From 5355f68f5f205e5488eb888fc1e5a9e0f11fcbac Mon Sep 17 00:00:00 2001 From: Robin van Emden Date: Sun, 17 Mar 2019 15:04:07 +0100 Subject: [PATCH] Version 0.9.8.1 Specified previous version of set.seed sampler with RNGversion() calls, to ensure CRAN devel check compatibility --- .Rbuildignore | 2 + DESCRIPTION | 2 +- NEWS.md | 5 + R/functions_utility.R | 2 +- cran-comments.md | 2 +- docs/articles/cmabs.html | 44 +-- docs/articles/cmabsoffline.html | 88 ++--- docs/articles/eckles_kaptein.html | 62 +-- docs/articles/epsilongreedy.html | 80 ++-- docs/articles/index.html | 4 +- docs/articles/introduction.html | 60 +-- docs/articles/mabs.html | 46 +-- docs/articles/ml10m.html | 244 ++++++------ docs/articles/offline_depaul_movies.html | 106 +++--- docs/articles/only_pkgdown/faq.html | 150 ++++---- docs/articles/replication.html | 156 ++++---- docs/articles/simpsons.html | 358 +++++++++--------- docs/articles/sutton_barto.html | 148 ++++---- docs/articles/website_optimization.html | 98 ++--- docs/authors.html | 4 +- docs/index.html | 18 +- docs/news/index.html | 31 +- docs/pkgdown.yml | 6 +- docs/reference/Agent.html | 4 +- docs/reference/Bandit.html | 4 +- docs/reference/BasicBernoulliBandit.html | 4 +- docs/reference/BasicGaussianBandit.html | 4 +- docs/reference/BootstrapTSPolicy.html | 4 +- docs/reference/ContextualBernoulliBandit.html | 4 +- docs/reference/ContextualBinaryBandit.html | 4 +- .../ContextualEpochGreedyPolicy.html | 4 +- .../ContextualEpsilonGreedyPolicy.html | 4 +- docs/reference/ContextualHybridBandit.html | 4 +- docs/reference/ContextualLinTSPolicy.html | 4 +- docs/reference/ContextualLinearBandit.html | 4 +- docs/reference/ContextualLogitBTSPolicy.html | 4 +- docs/reference/ContextualLogitBandit.html | 4 +- .../reference/ContextualPrecachingBandit.html | 4 +- docs/reference/ContextualTSProbitPolicy.html | 4 +- docs/reference/ContextualWheelBandit.html | 4 +- docs/reference/ContinuumBandit.html | 4 +- docs/reference/EpsilonFirstPolicy-1.png | Bin 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docs/reference/LinUCBHybridPolicy.html | 4 +- .../OfflineBootstrappedReplayBandit.html | 4 +- docs/reference/OfflineDirectMethodBandit.html | 4 +- docs/reference/OfflineDoublyRobustBandit.html | 4 +- .../OfflineLookupReplayEvaluatorBandit.html | 4 +- .../OfflinePropensityWeightingBandit.html | 4 +- .../OfflineReplayEvaluatorBandit.html | 4 +- docs/reference/OraclePolicy.html | 4 +- docs/reference/Plot.html | 4 +- docs/reference/Policy.html | 4 +- docs/reference/RandomPolicy-1.png | Bin 20536 -> 20345 bytes docs/reference/RandomPolicy.html | 6 +- docs/reference/Simulator.html | 4 +- docs/reference/SoftmaxPolicy-1.png | Bin 12625 -> 12625 bytes docs/reference/SoftmaxPolicy-2.png | Bin 13942 -> 13942 bytes docs/reference/SoftmaxPolicy.html | 6 +- docs/reference/ThompsonSamplingPolicy-1.png | Bin 13927 -> 13927 bytes docs/reference/ThompsonSamplingPolicy.html | 6 +- docs/reference/UCB1Policy.html | 4 +- docs/reference/UCB2Policy-1.png | Bin 11003 -> 11003 bytes docs/reference/UCB2Policy-2.png | Bin 13442 -> 13442 bytes docs/reference/UCB2Policy.html | 6 +- docs/reference/clipr.html | 4 +- .../data_table_factors_to_numeric.html | 4 +- docs/reference/dec-set.html | 4 +- docs/reference/formatted_difftime.html | 4 +- docs/reference/get_arm_context.html | 4 +- docs/reference/get_full_context.html | 4 +- docs/reference/inc-set.html | 4 +- docs/reference/ind.html | 4 +- docs/reference/index.html | 4 +- docs/reference/inv.html | 4 +- docs/reference/invgamma-1.png | Bin 12068 -> 12068 bytes docs/reference/invgamma.html | 4 +- docs/reference/invlogit.html | 4 +- docs/reference/is_rstudio.html | 4 +- docs/reference/mvrnorm.html | 4 +- docs/reference/one_hot.html | 4 +- docs/reference/ones_in_zeroes.html | 4 +- docs/reference/plot.history.html | 4 +- docs/reference/print.history.html | 4 +- docs/reference/prob_winner.html | 4 +- docs/reference/sample_one_of.html | 4 +- docs/reference/set_external.html | 4 +- docs/reference/sherman_morrisson.html | 4 +- docs/reference/sim_post.html | 4 +- docs/reference/sum_of.html | 4 +- docs/reference/summary.history.html | 4 +- docs/reference/value_remaining-1.png | Bin 10381 -> 10381 bytes docs/reference/value_remaining.html | 4 +- docs/reference/var_welford.html | 4 +- docs/reference/which_max_list.html | 4 +- docs/reference/which_max_tied.html | 4 +- vignettes/only_pkgdown/faq.Rmd | 4 - 115 files changed, 1024 insertions(+), 1012 deletions(-) diff --git a/.Rbuildignore b/.Rbuildignore index b9bf1bc..0493889 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,5 +1,7 @@ ^Meta$ ^doc$ +^vignettes/only_pkgdown$ +^vignettes/only_pkgdown.* ^demo/working_directory$ ^demo/working_directory.* contextual.Rproj diff --git a/DESCRIPTION b/DESCRIPTION index b7dfe85..d873958 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: contextual Type: Package Title: Simulation and Analysis of Contextual Multi-Armed Bandit Policies -Version: 0.9.8 +Version: 0.9.8.1 Authors@R: c(person("Robin", "van Emden", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5820-8638"), email = "robinvanemden@gmail.com"), person("Maurits", "Kaptein", role = "ctb", email = "m.c.kaptein@tilburguniversity.edu", diff --git a/NEWS.md b/NEWS.md index 90c3a58..476e3c2 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,8 @@ +contextual 0.9.8.1 +================== + +* Specified previous version of set.seed sampler with RNGversion() calls + contextual 0.9.8 ================ diff --git a/R/functions_utility.R b/R/functions_utility.R index 1c9df86..2a30490 100644 --- a/R/functions_utility.R +++ b/R/functions_utility.R @@ -421,7 +421,7 @@ get_full_context <- function(context, select_features = NULL, prepend_arm_matrix if(is.vector(X)) Xm <- X[select_features] else Xm <- X[select_features,] } - if(isTRUE(prepend_arm_vector)) Xv <- rbind(diag(k),Xv) + if(isTRUE(prepend_arm_matrix)) Xv <- rbind(diag(k),Xv) return(Xm) } diff --git a/cran-comments.md b/cran-comments.md index 5423d5e..1a97c25 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,4 +1,4 @@ -New submission. +Minor update adding "suppressWarnings(RNGversion("3.5.0"))" to ensure CRAN devel compatibility ## Test environments diff --git a/docs/articles/cmabs.html b/docs/articles/cmabs.html index 01052a6..e80c4b6 100644 --- a/docs/articles/cmabs.html +++ b/docs/articles/cmabs.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

Demo: Basic Synthetic cMAB Policies

Robin van Emden

-

2019-03-06

+

2019-03-17

Source: vignettes/cmabs.Rmd @@ -139,25 +139,25 @@

2019-03-06

-
library(contextual)
-
-horizon       <- 100L
-simulations   <- 100L
-
-bandit        <- ContextualLinearBandit$new(k = 4, d = 3, sigma = 0.3)
-
-# Linear CMAB policies comparison
-
-agents <- list(Agent$new(EpsilonGreedyPolicy$new(0.1), bandit, "EGreedy"),
-               Agent$new(ContextualEpsilonGreedyPolicy$new(0.1), bandit, "cEGreedy"),
-               Agent$new(ContextualLinTSPolicy$new(0.1), bandit, "LinTS"),
-               Agent$new(LinUCBDisjointOptimizedPolicy$new(0.6), bandit, "LinUCB"))
-
-simulation     <- Simulator$new(agents, horizon, simulations, do_parallel = TRUE)
-
-history        <- simulation$run()
-
-plot(history, type = "cumulative", rate = FALSE, legend_position = "topleft")
+
library(contextual)
+
+horizon       <- 100L
+simulations   <- 100L
+
+bandit        <- ContextualLinearBandit$new(k = 4, d = 3, sigma = 0.3)
+
+# Linear CMAB policies comparison
+
+agents <- list(Agent$new(EpsilonGreedyPolicy$new(0.1), bandit, "EGreedy"),
+               Agent$new(ContextualEpsilonGreedyPolicy$new(0.1), bandit, "cEGreedy"),
+               Agent$new(ContextualLinTSPolicy$new(0.1), bandit, "LinTS"),
+               Agent$new(LinUCBDisjointOptimizedPolicy$new(0.6), bandit, "LinUCB"))
+
+simulation     <- Simulator$new(agents, horizon, simulations, do_parallel = TRUE)
+
+history        <- simulation$run()
+
+plot(history, type = "cumulative", rate = FALSE, legend_position = "topleft")

@@ -172,7 +172,7 @@

2019-03-06

-

Site built with pkgdown 1.3.0.9000.

+

Site built with pkgdown 1.3.0.

diff --git a/docs/articles/cmabsoffline.html b/docs/articles/cmabsoffline.html index 3443825..050f34b 100644 --- a/docs/articles/cmabsoffline.html +++ b/docs/articles/cmabsoffline.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

Demo: Offline cMAB LinUCB evaluation

Robin van Emden

-

2019-03-06

+

2019-03-17

Source: vignettes/cmabsoffline.Rmd @@ -139,47 +139,47 @@

2019-03-06

-
library(contextual)
-library(data.table)
-
-# Import personalization data-set
-
-library(contextual); library(data.table)
-
-dt      <- fread("http://pwy.nl/d") # 0/1 reward, 10 arms, 100 features
-                                    # arms always start from 1
-
-#      z y x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15  .. x100
-#   1: 2 0  5  0  0 37  6  0  0  0  0  25   0   0   7   1   0  ..    0
-#   2: 8 0  1  3 36  0  0  0  0  0  0   0   0   1   0   0   0  ..   10
-#   3: . .  .  .  .  .  .  .  .  .  .   .   .   .   .   .   .  ..    .
-
-horizon     <- nrow(dt)
-simulations <- 1
-
-# Set up formula:       y      ~ z    | x1 + x2 + ..
-# In bandit parlance:   reward ~ arms | covariates or contextual features
-
-f       <- y ~ z | . - z
-
-# Instantiate Replay Bandit (Li, 2010)
-bandit  <- OfflineReplayEvaluatorBandit$new(formula = f, data = dt)
-
-# Bind Policies withs Bandits through Agents, add Agents to list
-agents  <- list(Agent$new(LinUCBDisjointOptimizedPolicy$new(0.01), bandit, "alpha = 0.01"),
-                Agent$new(LinUCBDisjointOptimizedPolicy$new(0.05), bandit, "alpha = 0.05"),
-                Agent$new(LinUCBDisjointOptimizedPolicy$new(0.1),  bandit, "alpha = 0.1"),
-                Agent$new(LinUCBDisjointOptimizedPolicy$new(1.0),  bandit, "alpha = 1.0"))
-
-# Instantiate a Simulator
-simulation <- Simulator$new(agents, horizon = nrow(dt), simulations = 1)
-
-# Run the simulation.
-history    <- simulation$run()
-
-# plot the results
-plot(history, type = "cumulative", regret = FALSE, rate = TRUE, 
-     legend_position = "bottomright", ylim = c(0,1))
+
library(contextual)
+library(data.table)
+
+# Import personalization data-set
+
+library(contextual); library(data.table)
+
+dt      <- fread("http://pwy.nl/d") # 0/1 reward, 10 arms, 100 features
+                                    # arms always start from 1
+
+#      z y x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12 x13 x14 x15  .. x100
+#   1: 2 0  5  0  0 37  6  0  0  0  0  25   0   0   7   1   0  ..    0
+#   2: 8 0  1  3 36  0  0  0  0  0  0   0   0   1   0   0   0  ..   10
+#   3: . .  .  .  .  .  .  .  .  .  .   .   .   .   .   .   .  ..    .
+
+horizon     <- nrow(dt)
+simulations <- 1
+
+# Set up formula:       y      ~ z    | x1 + x2 + ..
+# In bandit parlance:   reward ~ arms | covariates or contextual features
+
+f       <- y ~ z | . - z
+
+# Instantiate Replay Bandit (Li, 2010)
+bandit  <- OfflineReplayEvaluatorBandit$new(formula = f, data = dt)
+
+# Bind Policies withs Bandits through Agents, add Agents to list
+agents  <- list(Agent$new(LinUCBDisjointOptimizedPolicy$new(0.01), bandit, "alpha = 0.01"),
+                Agent$new(LinUCBDisjointOptimizedPolicy$new(0.05), bandit, "alpha = 0.05"),
+                Agent$new(LinUCBDisjointOptimizedPolicy$new(0.1),  bandit, "alpha = 0.1"),
+                Agent$new(LinUCBDisjointOptimizedPolicy$new(1.0),  bandit, "alpha = 1.0"))
+
+# Instantiate a Simulator
+simulation <- Simulator$new(agents, horizon = nrow(dt), simulations = 1)
+
+# Run the simulation.
+history    <- simulation$run()
+
+# plot the results
+plot(history, type = "cumulative", regret = FALSE, rate = TRUE, 
+     legend_position = "bottomright", ylim = c(0,1))

@@ -194,7 +194,7 @@

2019-03-06

-

Site built with pkgdown 1.3.0.9000.

+

Site built with pkgdown 1.3.0.

diff --git a/docs/articles/eckles_kaptein.html b/docs/articles/eckles_kaptein.html index f9114ea..7501a47 100644 --- a/docs/articles/eckles_kaptein.html +++ b/docs/articles/eckles_kaptein.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

Demo: MAB Replication Eckles & Kaptein (Bootstrap Thompson Sampling)

Robin van Emden

-

2019-03-06

+

2019-03-17

Source: vignettes/eckles_kaptein.Rmd @@ -139,34 +139,34 @@

2019-03-06

-
library(contextual)
-
-# Replication of THOMPSON SAMPLING WITH THE ONLINE BOOTSTRAP By Dean Eckles and Maurits Kaptein
-
-# This evaluations takes time - up to a few hours when run single core.
-
-# Running the script in parallel (for example, on 8 cores) 
-# shortens the evaluation time substantially.
-
-# https://arxiv.org/abs/1410.4009
-
-# Fig 2. Empirical regret for Thompson sampling and BTS in a K-armed binomial bandit problem.
-
-bandit             <- BasicBernoulliBandit$new(weights = c(0.5, rep(0.4,9)))
-
-agents             <- list(Agent$new(BootstrapTSPolicy$new(1000), bandit, "BTS 1000"),
-                           Agent$new(ThompsonSamplingPolicy$new(), bandit, "TS"))
-
-simulator          <- Simulator$new(agents        = agents,
-                                    do_parallel   = TRUE,
-                                    save_interval = 50,
-                                    set_seed      = 999,
-                                    horizon       = 1e+05,
-                                    simulations   = 1000)
-
-simulator$run()
-
-plot(simulator$history, log = "x")
+
library(contextual)
+
+# Replication of THOMPSON SAMPLING WITH THE ONLINE BOOTSTRAP By Dean Eckles and Maurits Kaptein
+
+# This evaluations takes time - up to a few hours when run single core.
+
+# Running the script in parallel (for example, on 8 cores) 
+# shortens the evaluation time substantially.
+
+# https://arxiv.org/abs/1410.4009
+
+# Fig 2. Empirical regret for Thompson sampling and BTS in a K-armed binomial bandit problem.
+
+bandit             <- BasicBernoulliBandit$new(weights = c(0.5, rep(0.4,9)))
+
+agents             <- list(Agent$new(BootstrapTSPolicy$new(1000), bandit, "BTS 1000"),
+                           Agent$new(ThompsonSamplingPolicy$new(), bandit, "TS"))
+
+simulator          <- Simulator$new(agents        = agents,
+                                    do_parallel   = TRUE,
+                                    save_interval = 50,
+                                    set_seed      = 999,
+                                    horizon       = 1e+05,
+                                    simulations   = 1000)
+
+simulator$run()
+
+plot(simulator$history, log = "x")

@@ -181,7 +181,7 @@

2019-03-06

-

Site built with pkgdown 1.3.0.9000.

+

Site built with pkgdown 1.3.0.

diff --git a/docs/articles/epsilongreedy.html b/docs/articles/epsilongreedy.html index faf8666..673ea2d 100644 --- a/docs/articles/epsilongreedy.html +++ b/docs/articles/epsilongreedy.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

Demo: Basic Epsilon Greedy

Robin van Emden

-

2019-03-06

+

2019-03-17

Source: vignettes/epsilongreedy.Rmd @@ -139,44 +139,44 @@

2019-03-06

-
library(contextual)
-
-policy             <- EpsilonGreedyPolicy$new(epsilon = 0.1)
-
-bandit             <- BasicBernoulliBandit$new(weights = c(0.6, 0.1, 0.1))
-agent              <- Agent$new(policy,bandit)
-
-simulator          <- Simulator$new(agents      = agent,
-                                    horizon     = 100,
-                                    simulations = 1000)
-                                    
-history            <- simulator$run()
-
-plot(history, type = "cumulative", regret = TRUE, disp = "ci",
-              traces_max = 100, traces_alpha = 0.1, traces = TRUE)
+
library(contextual)
+
+policy             <- EpsilonGreedyPolicy$new(epsilon = 0.1)
+
+bandit             <- BasicBernoulliBandit$new(weights = c(0.6, 0.1, 0.1))
+agent              <- Agent$new(policy,bandit)
+
+simulator          <- Simulator$new(agents      = agent,
+                                    horizon     = 100,
+                                    simulations = 1000)
+                                    
+history            <- simulator$run()
+
+plot(history, type = "cumulative", regret = TRUE, disp = "ci",
+              traces_max = 100, traces_alpha = 0.1, traces = TRUE)

-
summary(history)
-
-
Agents:
-
-  EpsilonGreedy
-
-Cumulative regret:
-
-         agent   t sims cum_regret cum_regret_var cum_regret_sd
- EpsilonGreedy 100 1000      8.951       116.7133      10.80339
-
-
-Cumulative reward:
-
-         agent   t sims cum_reward cum_reward_var cum_reward_sd
- EpsilonGreedy 100 1000      51.09       141.6215      11.90048
-
-
-Cumulative reward rate:
-
-         agent   t sims cur_reward cur_reward_var cur_reward_sd
- EpsilonGreedy 100 1000     0.5109       1.416215     0.1190048
+
summary(history)
+
+
Agents:
+
+  EpsilonGreedy
+
+Cumulative regret:
+
+         agent   t sims cum_regret cum_regret_var cum_regret_sd
+ EpsilonGreedy 100 1000      8.951       116.7133      10.80339
+
+
+Cumulative reward:
+
+         agent   t sims cum_reward cum_reward_var cum_reward_sd
+ EpsilonGreedy 100 1000      51.09       141.6215      11.90048
+
+
+Cumulative reward rate:
+
+         agent   t sims cur_reward cur_reward_var cur_reward_sd
+ EpsilonGreedy 100 1000     0.5109       1.416215     0.1190048
-

Site built with pkgdown 1.3.0.9000.

+

Site built with pkgdown 1.3.0.

diff --git a/docs/articles/index.html b/docs/articles/index.html index 6db3e95..639e0aa 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -66,7 +66,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -194,7 +194,7 @@

All vignettes

-

Site built with pkgdown 1.3.0.9000.

+

Site built with pkgdown 1.3.0.

diff --git a/docs/articles/introduction.html b/docs/articles/introduction.html index ddd7e3c..4157464 100644 --- a/docs/articles/introduction.html +++ b/docs/articles/introduction.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

Getting started: running simulations

Robin van Emden

-

2019-03-06

+

2019-03-17

Source: vignettes/introduction.Rmd @@ -157,33 +157,33 @@

  • EpsilonGreedyPolicy: explores one of the ads uniformly at random \(\epsilon\) of the time and exploits the ad with the best current click-through rate \(1 - \epsilon\) of the time. Here, we will set \(\epsilon = 0.4\).

    • Next, we assign the bandit and the two policy instances to two agents. Finally, we assign a list holding both agents to a Simulator instance, set the simulator’s horizon to four hundred and the number of repeats to ten thousand, run the simulation, and plot() its results:

    - +

    As can be observed in the figure above, within our horizon of \(T = 400\), EpsilonFirstPolicy has accumulated more rewards than EpsilonGreedytPolicy. It is easy to see why: The winning arm is better than the other two—by a margin. That means that EpsilonFirstPolicy has no difficulty in finding the optimal arm within its exploration period of one hundred impressions. Up to that point, EpsilonGreedyPolicy still had the advantage of a headstart, as it was already able to exploit for \(1- \epsilon\) or sixty percent of the time. But from one hundred impressions on, EpsilonFirstPolicy switches from full exploration to full exploitation mode. In contrast to EpsilonGreedyPolicy, it is now able to exploit the arm that proved best during exploration all of the time. As a result, it is able catch up with (and then surpass) the rewards accumulated by EpsilonGreedyPolicy within less than one hundred and fifty impressions.

    @@ -234,7 +234,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/mabs.html b/docs/articles/mabs.html index cb208fa..59320e3 100644 --- a/docs/articles/mabs.html +++ b/docs/articles/mabs.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: MAB Policies Comparison

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/mabs.Rmd @@ -139,26 +139,26 @@

    2019-03-06

    -
    library(contextual)
-
-prob_per_arm       <- c(0.9, 0.1, 0.1)
-horizon            <- 100
-simulations        <- 1000
-
-bandit             <- BasicBernoulliBandit$new(prob_per_arm)
-
-agents             <- list(Agent$new(OraclePolicy$new(), bandit),
-                           Agent$new(EpsilonGreedyPolicy$new(0.1), bandit),
-                           Agent$new(ThompsonSamplingPolicy$new(1.0, 1.0), bandit),
-                           Agent$new(Exp3Policy$new(0.1), bandit),
-                           Agent$new(GittinsBrezziLaiPolicy$new(), bandit),
-                           Agent$new(UCB1Policy$new(), bandit),
-                           Agent$new(UCB2Policy$new(0.1), bandit))
-
-simulation         <- Simulator$new(agents, horizon, simulations)
-history            <- simulation$run()
-
-plot(history, type = "cumulative")
    +
    library(contextual)
+
+prob_per_arm       <- c(0.9, 0.1, 0.1)
+horizon            <- 100
+simulations        <- 1000
+
+bandit             <- BasicBernoulliBandit$new(prob_per_arm)
+
+agents             <- list(Agent$new(OraclePolicy$new(), bandit),
+                           Agent$new(EpsilonGreedyPolicy$new(0.1), bandit),
+                           Agent$new(ThompsonSamplingPolicy$new(1.0, 1.0), bandit),
+                           Agent$new(Exp3Policy$new(0.1), bandit),
+                           Agent$new(GittinsBrezziLaiPolicy$new(), bandit),
+                           Agent$new(UCB1Policy$new(), bandit),
+                           Agent$new(UCB2Policy$new(0.1), bandit))
+
+simulation         <- Simulator$new(agents, horizon, simulations)
+history            <- simulation$run()
+
+plot(history, type = "cumulative")

    @@ -173,7 +173,7 @@

    2019-03-06

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/ml10m.html b/docs/articles/ml10m.html index 3d8d9e3..292ea83 100644 --- a/docs/articles/ml10m.html +++ b/docs/articles/ml10m.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: MovieLens 10M Dataset

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/ml10m.Rmd @@ -139,125 +139,125 @@

    2019-03-06

    -
    library(contextual)
-library(data.table)
-library(splitstackshape)
-library(RCurl)
-
-# Import MovieLens ml-10M ------------------------------------------------------------------------
-
-# Info: https://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/README.html
-
-movies_dat      <- "http://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/movies.dat"
-ratings_dat     <- "http://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/ratings.dat"
-
-movies_dat      <- readLines(movies_dat)
-movies_dat      <- gsub( "::", "~", movies_dat )
-movies_dat      <- paste0(movies_dat, collapse = "\n")
-movies_dat      <- fread(movies_dat, sep = "~", quote="")
-setnames(movies_dat, c("V1", "V2", "V3"), c("MovieID", "Name", "Type"))
-movies_dat      <- splitstackshape::cSplit_e(movies_dat, "Type", sep = "|", type = "character",
-                                             fill = 0, drop = TRUE)
-movies_dat[[3]] <- NULL
-
-ratings_dat     <- RCurl::getURL(ratings_dat)
-ratings_dat     <- readLines(textConnection(ratings_dat))
-ratings_dat     <- gsub( "::", "~", ratings_dat )
-ratings_dat     <- paste0(ratings_dat, collapse = "\n")
-ratings_dat     <- fread(ratings_dat, sep = "~", quote="")
-setnames(ratings_dat, c("V1", "V2", "V3", "V4"), c("UserID", "MovieID", "Rating", "Timestamp"))
-
-all_movies      <- ratings_dat[movies_dat, on=c(MovieID = "MovieID")]
-
-all_movies      <- na.omit(all_movies,cols=c("MovieID", "UserID"))
-
-rm(movies_dat,ratings_dat)
-
-# Data wrangling --------------------------------------------------------------------------------
-
-all_movies[, UserID   := as.numeric(as.factor(UserID))]
-
-count_movies    <- all_movies[,.(MovieCount = .N), by = MovieID]
-top_50          <- as.vector(count_movies[order(-MovieCount)][1:50]$MovieID)
-not_50          <- as.vector(count_movies[order(-MovieCount)][51:nrow(count_movies)]$MovieID)
-
-top_50_movies   <- all_movies[MovieID %in% top_50]
-
-# -----------------------------------------------------------------------------------------------
-
-# Create feature lookup tables - to speed up, MovieID and UserID are
-# ordered and lined up with the (dt/matrix) default index.
-
-# Arm features
-
-# MovieID of top 50 ordered from 1 to N as arms (Arms always start from 1)
-top_50_movies[, MovieID   := as.numeric(as.factor(MovieID))]
-arm_features    <- top_50_movies[,head(.SD, 1),by = MovieID][,c(1,6:24)]
-setorder(arm_features,MovieID)
-
-# User features
-
-# Count of categories for non-top-50 movies normalized per user
-user_features   <- all_movies[MovieID %in% not_50]
-user_features[, c("MovieID", "Rating", "Timestamp", "Name"):=NULL]
-user_features   <- user_features[, lapply(.SD, sum, na.rm=TRUE), by=UserID ]
-user_features[, total  := rowSums(.SD, na.rm = TRUE), .SDcols = 2:20]
-user_features[, 2:20 := lapply(.SD, function(x) x/total), .SDcols = 2:20]
-user_features$total <- NULL
-
-# Add users that were not in the set of non-top-50 movies (4 in 10m dataset)
-all_users <- as.data.table(unique(all_movies$UserID))
-user_features <- user_features[all_users, on=c(UserID = "V1")]
-user_features[is.na(user_features)] <- 0
-
-setorder(user_features,UserID)
-
-# ----------------------------------------------------------------------------------------------
-
-rm(all_movies, not_50, top_50, count_movies)
-
-# ----------------------------------------------------------------------------------------------
-
-# Contextual format
-
-top_50_movies[, t := .I]
-top_50_movies[, sim := 1]
-top_50_movies[, agent := "Offline"]
-top_50_movies[, choice := MovieID]
-top_50_movies[, reward := ifelse(Rating <= 4, 0, 1)]
-
-setorder(top_50_movies,Timestamp,Name)
-
-
-# Run simulation --------------------------------------------------------------------------------
-
-simulations <- 1
-horizon     <- 1000 #nrow(top_50_movies)
-
-bandit      <- OfflineLookupReplayEvaluatorBandit$new(top_50_movies,
-                                                      k             = 50,
-                                                      unique_col    = "UserID",
-                                                      shared_lookup = arm_features,
-                                                      unique_lookup = user_features)
-agents      <-
-  list(Agent$new(ThompsonSamplingPolicy$new(), bandit, "Thompson"),
-       Agent$new(UCB1Policy$new(), bandit, "UCB1"),
-       Agent$new(RandomPolicy$new(), bandit, "Random"),
-       Agent$new(LinUCBHybridOptimizedPolicy$new(0.9), bandit, "LinUCB Hyb 0.9"),
-       Agent$new(LinUCBDisjointOptimizedPolicy$new(2.1), bandit, "LinUCB Dis 2.1"))
-
-simulation  <-
-  Simulator$new(
-    agents           = agents,
-    simulations      = simulations,
-    horizon          = horizon,
-    reindex          = TRUE
-  )
-
-results  <- simulation$run()
-
-plot(results, type = "cumulative", regret = FALSE,
-     rate = TRUE, legend_position = "topleft")
    +
    library(contextual)
+library(data.table)
+library(splitstackshape)
+library(RCurl)
+
+# Import MovieLens ml-10M ------------------------------------------------------------------------
+
+# Info: https://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/README.html
+
+movies_dat      <- "http://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/movies.dat"
+ratings_dat     <- "http://d1ie9wlkzugsxr.cloudfront.net/data_movielens/ml-10M/ratings.dat"
+
+movies_dat      <- readLines(movies_dat)
+movies_dat      <- gsub( "::", "~", movies_dat )
+movies_dat      <- paste0(movies_dat, collapse = "\n")
+movies_dat      <- fread(movies_dat, sep = "~", quote="")
+setnames(movies_dat, c("V1", "V2", "V3"), c("MovieID", "Name", "Type"))
+movies_dat      <- splitstackshape::cSplit_e(movies_dat, "Type", sep = "|", type = "character",
+                                             fill = 0, drop = TRUE)
+movies_dat[[3]] <- NULL
+
+ratings_dat     <- RCurl::getURL(ratings_dat)
+ratings_dat     <- readLines(textConnection(ratings_dat))
+ratings_dat     <- gsub( "::", "~", ratings_dat )
+ratings_dat     <- paste0(ratings_dat, collapse = "\n")
+ratings_dat     <- fread(ratings_dat, sep = "~", quote="")
+setnames(ratings_dat, c("V1", "V2", "V3", "V4"), c("UserID", "MovieID", "Rating", "Timestamp"))
+
+all_movies      <- ratings_dat[movies_dat, on=c(MovieID = "MovieID")]
+
+all_movies      <- na.omit(all_movies,cols=c("MovieID", "UserID"))
+
+rm(movies_dat,ratings_dat)
+
+# Data wrangling --------------------------------------------------------------------------------
+
+all_movies[, UserID   := as.numeric(as.factor(UserID))]
+
+count_movies    <- all_movies[,.(MovieCount = .N), by = MovieID]
+top_50          <- as.vector(count_movies[order(-MovieCount)][1:50]$MovieID)
+not_50          <- as.vector(count_movies[order(-MovieCount)][51:nrow(count_movies)]$MovieID)
+
+top_50_movies   <- all_movies[MovieID %in% top_50]
+
+# -----------------------------------------------------------------------------------------------
+
+# Create feature lookup tables - to speed up, MovieID and UserID are
+# ordered and lined up with the (dt/matrix) default index.
+
+# Arm features
+
+# MovieID of top 50 ordered from 1 to N as arms (Arms always start from 1)
+top_50_movies[, MovieID   := as.numeric(as.factor(MovieID))]
+arm_features    <- top_50_movies[,head(.SD, 1),by = MovieID][,c(1,6:24)]
+setorder(arm_features,MovieID)
+
+# User features
+
+# Count of categories for non-top-50 movies normalized per user
+user_features   <- all_movies[MovieID %in% not_50]
+user_features[, c("MovieID", "Rating", "Timestamp", "Name"):=NULL]
+user_features   <- user_features[, lapply(.SD, sum, na.rm=TRUE), by=UserID ]
+user_features[, total  := rowSums(.SD, na.rm = TRUE), .SDcols = 2:20]
+user_features[, 2:20 := lapply(.SD, function(x) x/total), .SDcols = 2:20]
+user_features$total <- NULL
+
+# Add users that were not in the set of non-top-50 movies (4 in 10m dataset)
+all_users <- as.data.table(unique(all_movies$UserID))
+user_features <- user_features[all_users, on=c(UserID = "V1")]
+user_features[is.na(user_features)] <- 0
+
+setorder(user_features,UserID)
+
+# ----------------------------------------------------------------------------------------------
+
+rm(all_movies, not_50, top_50, count_movies)
+
+# ----------------------------------------------------------------------------------------------
+
+# Contextual format
+
+top_50_movies[, t := .I]
+top_50_movies[, sim := 1]
+top_50_movies[, agent := "Offline"]
+top_50_movies[, choice := MovieID]
+top_50_movies[, reward := ifelse(Rating <= 4, 0, 1)]
+
+setorder(top_50_movies,Timestamp,Name)
+
+
+# Run simulation --------------------------------------------------------------------------------
+
+simulations <- 1
+horizon     <- 1000 #nrow(top_50_movies)
+
+bandit      <- OfflineLookupReplayEvaluatorBandit$new(top_50_movies,
+                                                      k             = 50,
+                                                      unique_col    = "UserID",
+                                                      shared_lookup = arm_features,
+                                                      unique_lookup = user_features)
+agents      <-
+  list(Agent$new(ThompsonSamplingPolicy$new(), bandit, "Thompson"),
+       Agent$new(UCB1Policy$new(), bandit, "UCB1"),
+       Agent$new(RandomPolicy$new(), bandit, "Random"),
+       Agent$new(LinUCBHybridOptimizedPolicy$new(0.9), bandit, "LinUCB Hyb 0.9"),
+       Agent$new(LinUCBDisjointOptimizedPolicy$new(2.1), bandit, "LinUCB Dis 2.1"))
+
+simulation  <-
+  Simulator$new(
+    agents           = agents,
+    simulations      = simulations,
+    horizon          = horizon,
+    reindex          = TRUE
+  )
+
+results  <- simulation$run()
+
+plot(results, type = "cumulative", regret = FALSE,
+     rate = TRUE, legend_position = "topleft")

    @@ -272,7 +272,7 @@

    2019-03-06

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/offline_depaul_movies.html b/docs/articles/offline_depaul_movies.html index 51b1aad..8a5a1a2 100644 --- a/docs/articles/offline_depaul_movies.html +++ b/docs/articles/offline_depaul_movies.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: Offline cMAB: CarsKit DePaul Movie Dataset

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/offline_depaul_movies.Rmd @@ -139,56 +139,56 @@

    2019-03-06

    -
    library(contextual)
-library(data.table)
-
-# Import personalization data-set
-
-# Info: https://d1ie9wlkzugsxr.cloudfront.net/data_irecsys_CARSKit/Movie_DePaulMovie/README.txt
-
-url         <- "http://d1ie9wlkzugsxr.cloudfront.net/data_irecsys_CARSKit/Movie_DePaulMovie/ratings.csv"
-data        <- fread(url, stringsAsFactors=TRUE)
-
-# Convert data
-
-data        <- contextual::one_hot(data, cols = c("Time","Location","Companion"), sparsifyNAs = TRUE)
-data[, itemid := as.numeric(itemid)]
-data[, rating := ifelse(rating <= 3, 0, 1)]
-
-# Set simulation parameters.
-simulations <- 10  # here, "simulations" represents the number of boostrap samples
-horizon     <- nrow(data)
-
-# Initiate Replay bandit with 10 arms and 100 context dimensions
-# Arms always start with 1 for the first arm
-log_S       <- data
-formula     <- formula("rating ~ itemid | Time_Weekday + Time_Weekend + Location_Cinema + 
-                                          Location_Home + Companion_Alone + Companion_Family + 
-                                          Companion_Partner")
-bandit      <- OfflineBootstrappedReplayBandit$new(formula = formula, data = data)
-
-# Define agents.
-agents      <-
-  list(Agent$new(RandomPolicy$new(), bandit, "Random"),
-       Agent$new(EpsilonGreedyPolicy$new(0.03), bandit, "EGreedy 0.05"),
-       Agent$new(ThompsonSamplingPolicy$new(), bandit, "ThompsonSampling"),
-       Agent$new(LinUCBDisjointOptimizedPolicy$new(0.37), bandit, "LinUCB 0.37"))
-
-# Initialize the simulation.
-simulation  <-
-  Simulator$new(
-    agents           = agents,
-    simulations      = simulations,
-    horizon          = horizon
-  )
-
-# Run the simulation.
-# Takes +- 5 minutes: bootstrapbandit loops through arms x horizon x simulations (times nr of agents).
-sim  <- simulation$run()
-
-# plot the results
-plot(sim, type = "cumulative", regret = FALSE, rate = TRUE,
-         legend_position = "topleft", ylim=c(0.48,0.87))
    +
    library(contextual)
+library(data.table)
+
+# Import personalization data-set
+
+# Info: https://d1ie9wlkzugsxr.cloudfront.net/data_irecsys_CARSKit/Movie_DePaulMovie/README.txt
+
+url         <- "http://d1ie9wlkzugsxr.cloudfront.net/data_irecsys_CARSKit/Movie_DePaulMovie/ratings.csv"
+data        <- fread(url, stringsAsFactors=TRUE)
+
+# Convert data
+
+data        <- contextual::one_hot(data, cols = c("Time","Location","Companion"), sparsifyNAs = TRUE)
+data[, itemid := as.numeric(itemid)]
+data[, rating := ifelse(rating <= 3, 0, 1)]
+
+# Set simulation parameters.
+simulations <- 10  # here, "simulations" represents the number of boostrap samples
+horizon     <- nrow(data)
+
+# Initiate Replay bandit with 10 arms and 100 context dimensions
+# Arms always start with 1 for the first arm
+log_S       <- data
+formula     <- formula("rating ~ itemid | Time_Weekday + Time_Weekend + Location_Cinema + 
+                                          Location_Home + Companion_Alone + Companion_Family + 
+                                          Companion_Partner")
+bandit      <- OfflineBootstrappedReplayBandit$new(formula = formula, data = data)
+
+# Define agents.
+agents      <-
+  list(Agent$new(RandomPolicy$new(), bandit, "Random"),
+       Agent$new(EpsilonGreedyPolicy$new(0.03), bandit, "EGreedy 0.05"),
+       Agent$new(ThompsonSamplingPolicy$new(), bandit, "ThompsonSampling"),
+       Agent$new(LinUCBDisjointOptimizedPolicy$new(0.37), bandit, "LinUCB 0.37"))
+
+# Initialize the simulation.
+simulation  <-
+  Simulator$new(
+    agents           = agents,
+    simulations      = simulations,
+    horizon          = horizon
+  )
+
+# Run the simulation.
+# Takes +- 5 minutes: bootstrapbandit loops through arms x horizon x simulations (times nr of agents).
+sim  <- simulation$run()
+
+# plot the results
+plot(sim, type = "cumulative", regret = FALSE, rate = TRUE,
+         legend_position = "topleft", ylim=c(0.48,0.87))

    @@ -203,7 +203,7 @@

    2019-03-06

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/only_pkgdown/faq.html b/docs/articles/only_pkgdown/faq.html index f0b41d0..61067a2 100644 --- a/docs/articles/only_pkgdown/faq.html +++ b/docs/articles/only_pkgdown/faq.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Development FAQ

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/only_pkgdown/faq.Rmd @@ -164,50 +164,50 @@

    What is this “self$theta_to_arms” list I see in some Policies?

    In many of contextual’s Policy’s set_parameters() initialisation function, a parameter list is being assigned to a “self$theta_to_arms”. But the parameters themselves are later only available through self$theta.

    The following source code comments how this little helper variable is used:

    -
    EpsilonFirstPolicy              <- R6::R6Class(
-  inherit = Policy,
-  public = list(
-    first = NULL,
-    class_name = "EpsilonFirstPolicy",
-    initialize = function(epsilon = 0.1, N = 1000) {
-      super$initialize()
-      self$first                <- ceiling(epsilon*N)
-    },
-    set_parameters = function(context_params) {
-
-      self$theta_to_arms        <- list('n' = 0, 'mean' = 0)
-
-      # Here we define a list with 'n' and 'mean' theta parameters to each
-      # arm through helper variable self$theta_to_arms. That is, when the
-      # number of arms is 'k', the above would equal:
-
-      # self$theta <- list(n = rep(list(0,k)), 'mean' = rep(list(0,k)))
-
-      # ... which would also work just fine, but is much less concise.
-
-      # When assigning both to self$theta directly & via self$theta_to_arms,
-      # make sure to do it in that particular order.
-    },
-    get_action = function(t, context) {
-      if (sum_of(self$theta$n) < self$first) {
-        action$choice           <- sample.int(context$k, 1, replace = TRUE)
-      } else {
-        action$choice           <- max_in(self$theta$mean)
-      }
-      action
-    },
-    set_reward = function(t, context, action, reward) {
-      arm                       <- action$choice
-      reward                    <- reward$reward
-      inc(self$theta$n[[arm]])  <- 1
-      if (sum_of(self$theta$n) < self$first - 1) {
-        inc(self$theta$mean[[arm]]) <-
-           (reward - self$theta$mean[[arm]]) / self$theta$n[[arm]]
-      }
-      self$theta
-    }
-  )
-)
    +
    EpsilonFirstPolicy              <- R6::R6Class(
+  inherit = Policy,
+  public = list(
+    first = NULL,
+    class_name = "EpsilonFirstPolicy",
+    initialize = function(epsilon = 0.1, N = 1000) {
+      super$initialize()
+      self$first                <- ceiling(epsilon*N)
+    },
+    set_parameters = function(context_params) {
+
+      self$theta_to_arms        <- list('n' = 0, 'mean' = 0)
+
+      # Here we define a list with 'n' and 'mean' theta parameters to each
+      # arm through helper variable self$theta_to_arms. That is, when the
+      # number of arms is 'k', the above would equal:
+
+      # self$theta <- list(n = rep(list(0,k)), 'mean' = rep(list(0,k)))
+
+      # ... which would also work just fine, but is much less concise.
+
+      # When assigning both to self$theta directly & via self$theta_to_arms,
+      # make sure to do it in that particular order.
+    },
+    get_action = function(t, context) {
+      if (sum_of(self$theta$n) < self$first) {
+        action$choice           <- sample.int(context$k, 1, replace = TRUE)
+      } else {
+        action$choice           <- max_in(self$theta$mean)
+      }
+      action
+    },
+    set_reward = function(t, context, action, reward) {
+      arm                       <- action$choice
+      reward                    <- reward$reward
+      inc(self$theta$n[[arm]])  <- 1
+      if (sum_of(self$theta$n) < self$first - 1) {
+        inc(self$theta$mean[[arm]]) <-
+           (reward - self$theta$mean[[arm]]) / self$theta$n[[arm]]
+      }
+      self$theta
+    }
+  )
+)

    @@ -223,22 +223,22 @@

    How do I use R packages within custom Bandits and Policies?

    If one of your custom Bandits or Policies requires a specific R package, use Simulator’s include_packages option to distribute the package(s) to each of a Simulator intance’s workers:

    - +

    It is then good practice to use a double colon operator to access some function from any included packages:

    - +

    @@ -256,19 +256,19 @@

    What is this public “class_name” member in every Bandit and Policy?

    Contextual uses the public “class_name” member internally to keep track of Policy’s and Bandit’s, and to, among others, generate names for Agents’ that have not been named explicitly. So don’t forget to include it in your own custom Bandit’s and Policies!

    - +

    @@ -307,7 +307,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/replication.html b/docs/articles/replication.html index cf6f2c3..aa9adae 100644 --- a/docs/articles/replication.html +++ b/docs/articles/replication.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Offline evaluation: Replication of Li et al 2010

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/replication.Rmd @@ -165,83 +165,83 @@

    Custom bandit and policies

    With the Yahoo! data imported into the MonetDB server, the next step was to create a custom offline YahooBandit plus seven Policy subclasses implementing the policies described in the Li et al 2010 paper. Though most of these policies were already implemented in contextual, the fact that only a subset of all 271 articles or arms are shown to a visitor at a time meant we needed to make some minor changes to contextual’s exisiting classes to make the policies run smoothly on a continually shifting pool of active arms.

    To facilitate these shifting arms, YahooBandit makes use of an self$arm_lookup table listing all 271 arms. This table enables the bandit to look up the currently active arms’ indexes from the shifting set of article ID’s as specified in the dataset for each time step \(t\), and return these indexes to the policies under evaluation:

    -
        get_context = function(index) {
-      ...
-      # Retrieve the index of all arms this row/event.
-      arm_indices_this_event  <- seq(10, 184, by = 7)
-      article_ids             <- row[arm_indices_this_event]
-      article_ids             <- article_ids[!is.na(article_ids)]
-      article_ids             <- match(article_ids,self$arm_lookup)
-      ...
-      context <- list(
-        k = self$k,
-        d = self$d,
-        unique = self$unique, # Indexes of disjoint arms (user features)
-        shared = self$shared, # Indexes of shared arms (article features)
-        arms = article_ids,   # Indexes of arms this event.
-        X = X
-      )
-    }
    +
        get_context = function(index) {
+      ...
+      # Retrieve the index of all arms this row/event.
+      arm_indices_this_event  <- seq(10, 184, by = 7)
+      article_ids             <- row[arm_indices_this_event]
+      article_ids             <- article_ids[!is.na(article_ids)]
+      article_ids             <- match(article_ids,self$arm_lookup)
+      ...
+      context <- list(
+        k = self$k,
+        d = self$d,
+        unique = self$unique, # Indexes of disjoint arms (user features)
+        shared = self$shared, # Indexes of shared arms (article features)
+        arms = article_ids,   # Indexes of arms this event.
+        X = X
+      )
+    }

    The policy classes then use this information to select and update only the currently active subset of arms. For instance, in YahooEpsilonGreedyPolicy’s get_action():

    -
        get_action = function(t, context) {
-      if (runif(1) > self$epsilon) {
-        # get the max of context$arms *currently in play*
-        max_index          <- context$arms[max_in(theta$mean[context$arms])]
-        self$action$choice <- max_index
-      } else {
-        # sample from the arms *currently in play*
-        self$action$choice <- sample(context$arms, 1)
-      }
-      self$action
-    }
    +
        get_action = function(t, context) {
+      if (runif(1) > self$epsilon) {
+        # get the max of context$arms *currently in play*
+        max_index          <- context$arms[max_in(theta$mean[context$arms])]
+        self$action$choice <- max_index
+      } else {
+        # sample from the arms *currently in play*
+        self$action$choice <- sample(context$arms, 1)
+      }
+      self$action
+    }

    On completing the implementation of the aforementioned seven custom policy subclasses (Random, EGreedy, EGreedySeg, LinUCBDis, LinUCBHyb, UCB1 and UCB1Seg) we then assigned them to six simulations—one for each of the six (0, 30, 20, 10, 5 and 1 percent) levels of sparsity defined in the original paper. This resulted in \(7\times6=42\) Agents, which were then run on the offline dataset as follows:

    -
    simulations             <- 1
-horizon                 <- 37.45e6
-...
-con <- DBI::dbConnect(MonetDB.R(), host=monetdb_host, dbname=monetdb_dbname,
-                                   user=monetdb_user, password=monetdb_pass)
-
-message(paste0("MonetDB: connection to '",dbListTables(con),"' succesful!"))
-
-arm_lookup_table <-
-  as.matrix(DBI::dbGetQuery(con, "SELECT DISTINCT article_id FROM yahoo"))
-
-arm_lookup_table <- rev(as.vector(arm_lookup_table))
-
-bandit <- YahooBandit$new(k = 217L, unique = c(1:6), shared = c(7:12),
-                          arm_lookup = arm_lookup_table, host = monetdb_host,
-                          dbname = monetdb_dbname, user = monetdb_user,
-                          password = monetdb_pass, buffer_size = buffer_size)
-
-agents <-
-  list (Agent$new(YahooLinUCBDisjointPolicy$new(0.2),
-                  bandit, name = "LinUCB Dis",  sparse = 0.99),
-        Agent$new(YahooLinUCBHybridPolicy$new(0.2),
-                  bandit, name = "LinUCB Hyb",  sparse = 0.99),
-        Agent$new(YahooEpsilonGreedyPolicy$new(0.3),
-                  bandit, name = "EGreedy",     sparse = 0.99),
-        Agent$new(YahooEpsilonGreedySegPolicy$new(0.3),
-                  bandit, name = "EGreedySeg",  sparse = 0.99),
-        Agent$new(YahooUCB1AlphaPolicy$new(0.4),
-                  bandit, name = "UCB1",        sparse = 0.99),
-        Agent$new(YahooUCB1AlphaSegPolicy$new(0.4),
-                  bandit, name = "UCB1Seg",     sparse = 0.99),
-        ...
-        Agent$new(YahooRandomPolicy$new(),
-                  bandit, name = "Random"))
-
-simulation <- Simulator$new(
-    agents,
-    simulations = simulations,
-    horizon = horizon,
-    do_parallel = TRUE,
-    worker_max = worker_max,
-    reindex = TRUE,
-    progress_file = TRUE,
-    include_packages = c("MonetDB.R"))
-
-history  <- simulation$run()
-...
    +
    simulations             <- 1
+horizon                 <- 37.45e6
+...
+con <- DBI::dbConnect(MonetDB.R(), host=monetdb_host, dbname=monetdb_dbname,
+                                   user=monetdb_user, password=monetdb_pass)
+
+message(paste0("MonetDB: connection to '",dbListTables(con),"' succesful!"))
+
+arm_lookup_table <-
+  as.matrix(DBI::dbGetQuery(con, "SELECT DISTINCT article_id FROM yahoo"))
+
+arm_lookup_table <- rev(as.vector(arm_lookup_table))
+
+bandit <- YahooBandit$new(k = 217L, unique = c(1:6), shared = c(7:12),
+                          arm_lookup = arm_lookup_table, host = monetdb_host,
+                          dbname = monetdb_dbname, user = monetdb_user,
+                          password = monetdb_pass, buffer_size = buffer_size)
+
+agents <-
+  list (Agent$new(YahooLinUCBDisjointPolicy$new(0.2),
+                  bandit, name = "LinUCB Dis",  sparse = 0.99),
+        Agent$new(YahooLinUCBHybridPolicy$new(0.2),
+                  bandit, name = "LinUCB Hyb",  sparse = 0.99),
+        Agent$new(YahooEpsilonGreedyPolicy$new(0.3),
+                  bandit, name = "EGreedy",     sparse = 0.99),
+        Agent$new(YahooEpsilonGreedySegPolicy$new(0.3),
+                  bandit, name = "EGreedySeg",  sparse = 0.99),
+        Agent$new(YahooUCB1AlphaPolicy$new(0.4),
+                  bandit, name = "UCB1",        sparse = 0.99),
+        Agent$new(YahooUCB1AlphaSegPolicy$new(0.4),
+                  bandit, name = "UCB1Seg",     sparse = 0.99),
+        ...
+        Agent$new(YahooRandomPolicy$new(),
+                  bandit, name = "Random"))
+
+simulation <- Simulator$new(
+    agents,
+    simulations = simulations,
+    horizon = horizon,
+    do_parallel = TRUE,
+    worker_max = worker_max,
+    reindex = TRUE,
+    progress_file = TRUE,
+    include_packages = c("MonetDB.R"))
+
+history  <- simulation$run()
+...

    @@ -267,7 +267,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/simpsons.html b/docs/articles/simpsons.html index 4cf077a..e0f467e 100644 --- a/docs/articles/simpsons.html +++ b/docs/articles/simpsons.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: Bandits, Propensity Weighting & Simpson’s Paradox in R

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/simpsons.Rmd @@ -140,24 +140,24 @@

    2019-03-06

    Imagine a website with Sport and Movie related articles where the “actual” preference of men and women for Sport and Movie articles is the following:

    -
    Contexts   | Sport (arm) |  Movie (arm)
------------------------------------------
-Male       | 0.4         |  0.3
-Female     | 0.8         |  0.7
    +
    Contexts   | Sport (arm) |  Movie (arm)
+-----------------------------------------
+Male       | 0.4         |  0.3
+Female     | 0.8         |  0.7

    In other words, both Male and Female visitors actually prefer Sports articles over Movie articles. When visitors are randomly assigned to types of articles, the overall CTR rate per category reflects this:

    -
    Contexts   | Sport (arm) |  Movie (arm)
------------------------------------------
-Male       | 0.4 x 0.5   |  0.3 x 0.5
-Female     | 0.8 x 0.5   |  0.7 x 0.5
------------------------------------------
-CTR total  | 0.6         |  0.5
    +
    Contexts   | Sport (arm) |  Movie (arm)
+-----------------------------------------
+Male       | 0.4 x 0.5   |  0.3 x 0.5
+Female     | 0.8 x 0.5   |  0.7 x 0.5
+-----------------------------------------
+CTR total  | 0.6         |  0.5

    Now suggest the site’s editor just “knows” that men like sports, and women like movie related articles. So the editor has some business logic implemented, assigning Movie related articles, on average, to 75% of Female visitors, and Sports articles, on average, to 75% of Male visitors:

    -
    Contexts   | Sport (arm) |  Movie (arm)
------------------------------------------
-Male       | 0.4 x 0.75  |  0.3 x 0.25
-Female     | 0.8 x 0.25  |  0.7 x 0.75
------------------------------------------
-CTR total  | 0.5         |  0.6
    +
    Contexts   | Sport (arm) |  Movie (arm)
+-----------------------------------------
+Male       | 0.4 x 0.75  |  0.3 x 0.25
+Female     | 0.8 x 0.25  |  0.7 x 0.75
+-----------------------------------------
+CTR total  | 0.5         |  0.6

    This results in a higher CTR for movies than for Sports related articles - even though these CTR’s do not actually reflect the overall preferences of website visitors, but rather the editor’s prejudice.

    A clear example of Simpson’s Paradox!

    Below an R code based illustration (making use of our “contextual” bandit package) of how Simpson’s Paradox could give rise to biased logged data, resulting in biased offline evaluations of bandit policies. Next, we demonstrate how inverse propensity weighting can help make such data usable for offline evaluation after all.

    @@ -165,197 +165,197 @@

    2019-03-06

    Original bandit weights

    Set up simulation bandit weights representing Male and Female actual preferences for Sports and Movies:

    -
     
-horizon                           <- 10000L
-simulations                       <- 1L
-
-#                    S----M------------> Arm 1:   Sport
-#                    |    |              Arm 2:   Movie
-#                    |    |
-weights <- matrix( c(0.4, 0.3,    #-----> Context: Male
-                     0.8, 0.7),   #-----> Context: Female
- 
-                     nrow = 2, ncol = 2, byrow = TRUE)
    +
     
+horizon                           <- 10000L
+simulations                       <- 1L
+
+#                    S----M------------> Arm 1:   Sport
+#                    |    |              Arm 2:   Movie
+#                    |    |
+weights <- matrix( c(0.4, 0.3,    #-----> Context: Male
+                     0.8, 0.7),   #-----> Context: Female
+ 
+                     nrow = 2, ncol = 2, byrow = TRUE)

    These weights will be fed to contextual’s ContextualBernoulliBandit so it can simulate clicks by Male and Female according to their preferences per category.

    Generate data by running a fully random online policy

    Let’s first run contextual’s basic random policy against the bandit that models actual visitor’s preferences. This random policy assigns Males and Females fully at random to either Sport or Movie articles:

    - +

    The results are clear: when running the random policy, the logged data accurately represents visitor’s preferences.

    Using the random policy’s offline logged data to evaluate another policy

    The previous simulation produced a data.table with fully randomised historical data. Let’s use this data to evaluate some other policy:

    - +

    Accurate numbers again: clearly, the logged data from a randomizing policy can be used to test other ‘off-policy’ algorithms.

    Generate data by running a biased online policy

    -

    Now suggest some editor just “knows’ that men like Sport, and women like Movie. So some business logic was added to the site assigning Movie related articles, on average, to 75% of Female visitors, and Sport articles, on average, to 75% of Male visitors.

    +

    Now suggest some editor just "knows’ that men like Sport, and women like Movie. So some business logic was added to the site assigning Movie related articles, on average, to 75% of Female visitors, and Sport articles, on average, to 75% of Male visitors.

    This business logic might be implemented through the following policy:

    - +

    Now run this policy against the Bandit modeling actual visitor preferences:

    - +

    Clearly, the BiasedPolicy gives rise to, well, biased results! If you’d only be able to look at the data, without knowing of the biased business logic, you’d falsely conclude Sports is more popular then Movies, overall.

    Using the biased policy’s offline logged data to evaluate another policy

    This time, the simulation generated a data.table with biased data. Let’s see what happens if we use this data to evaluate some other policy:

    - +

    The bias has propagated itself! So, does that mean it is not possible to use the “biased” data to evaluate other, off-line policies? That would severely limit the number of data sets for use in offline evaluation.

    Repairing the biased policy’s logged data with inverse probability weights

    Luckily, inverse propensity score weighting enables us to use propensity scores to obtain unbiased estimates of the original preferences of Male and Female visitors. That is, since our biased policy actually saved the propensity (“the probability of a unit being assigned to a particular treatment or category”) with which a certain category was chosen, we can correct for this bias while “replaying” the data. In “contextual”, there are several types of offline bandits that are able to use either such presaved propensities, or estimate propensities based on certain properties of the dataset. Here, we use its basic “OfflinePropensityWeightingBandit”:

    - +

    Hurray - inverse propensity score weighting has removed the bias! In other words: if and where possible, save propensity scores to your log files when experimenting with online policies. You will thank yourself at a later time!

    @@ -383,7 +383,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/sutton_barto.html b/docs/articles/sutton_barto.html index d22d471..99cf1d7 100644 --- a/docs/articles/sutton_barto.html +++ b/docs/articles/sutton_barto.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: Replication Sutton & Barto, Reinforcement Learning: An Introduction, Chapter 2

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/sutton_barto.Rmd @@ -139,107 +139,107 @@

    2019-03-06

    -

    Simulation of the multi-armed Bandit examples in chapter 2 of “Reinforcement Learning: An Introduction” by Sutton and Barto, 2nd ed. (Version: 2018)

    +

    Simulation of the multi-armed Bandit examples in chapter 2 of “Reinforcement Learning: An Introduction” by Sutton and Barto, 2nd ed. (Version: 2018)

    This book is available here: Sutton&Barto

    2.3 The 10-armed Testbed

    Generate the 10 arms.

    - +

    The violin plot

    Install ggplot2 and ggnormalviolin libraries to be able to generate Figure 2.1.

    -
    
-if(!require(ggplot2)) install.packages("ggplot2")
-if(!require(ggnormalviolin)) devtools::install_github("wjschne/ggnormalviolin")
-
-library(ggplot2)
-library(ggnormalviolin)
-
-print(ggplot(data = data.frame(dist_mean = mus, dist_sd = sigmas, dist = factor((1:10))), 
-             aes(x = dist, mu = dist_mean, sigma = dist_sd)) + ylab("Reward distribution") +
-             geom_normalviolin() + theme(legend.position = "none") + 
-             xlab("Action") + geom_hline(aes(yintercept = 0)))
    +
    
+if(!require(ggplot2)) install.packages("ggplot2")
+if(!require(ggnormalviolin)) devtools::install_github("wjschne/ggnormalviolin")
+
+library(ggplot2)
+library(ggnormalviolin)
+
+print(ggplot(data = data.frame(dist_mean = mus, dist_sd = sigmas, dist = factor((1:10))), 
+             aes(x = dist, mu = dist_mean, sigma = dist_sd)) + ylab("Reward distribution") +
+             geom_normalviolin() + theme(legend.position = "none") + 
+             xlab("Action") + geom_hline(aes(yintercept = 0)))

    The epsilon greedy plot

    -
    
-agents          <- list(Agent$new(EpsilonGreedyPolicy$new(0),    bandit, "e = 0, greedy"),
-                        Agent$new(EpsilonGreedyPolicy$new(0.1),  bandit, "e = 0.1"),
-                        Agent$new(EpsilonGreedyPolicy$new(0.01), bandit, "e = 0.01"))
-
-simulator       <- Simulator$new(agents = agents, horizon = 1000, simulations = 2000)
-history         <- simulator$run()
-
-plot(history, type = "average", regret = FALSE, lwd = 1, legend_position = "bottomright")
-plot(history, type = "optimal", lwd = 1, legend_position = "bottomright")
    +
    
+agents          <- list(Agent$new(EpsilonGreedyPolicy$new(0),    bandit, "e = 0, greedy"),
+                        Agent$new(EpsilonGreedyPolicy$new(0.1),  bandit, "e = 0.1"),
+                        Agent$new(EpsilonGreedyPolicy$new(0.01), bandit, "e = 0.01"))
+
+simulator       <- Simulator$new(agents = agents, horizon = 1000, simulations = 2000)
+history         <- simulator$run()
+
+plot(history, type = "average", regret = FALSE, lwd = 1, legend_position = "bottomright")
+plot(history, type = "optimal", lwd = 1, legend_position = "bottomright")

    2.6 - Optimistic values

    - +

    2.7 - Upper-Confidence-Bound Action Selection

    -
    
-agents          <- list(Agent$new(EpsilonGreedyPolicy$new(0.1),  bandit, "EGreedy"),
-                        Agent$new(UCB1Policy$new(),   bandit,            "UCB1"))
-
-simulator       <- Simulator$new(agents = agents, horizon = 1000, simulations = 2000)
-history         <- simulator$run()
-
-plot(history, type = "average", regret = FALSE, lwd = 1, legend_position = "bottomright")
    +
    
+agents          <- list(Agent$new(EpsilonGreedyPolicy$new(0.1),  bandit, "EGreedy"),
+                        Agent$new(UCB1Policy$new(),   bandit,            "UCB1"))
+
+simulator       <- Simulator$new(agents = agents, horizon = 1000, simulations = 2000)
+history         <- simulator$run()
+
+plot(history, type = "average", regret = FALSE, lwd = 1, legend_position = "bottomright")

    2.8 - Gradient Bandit Algorithms

    - +

    @@ -270,7 +270,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/articles/website_optimization.html b/docs/articles/website_optimization.html index a7ae5f9..6eedc52 100644 --- a/docs/articles/website_optimization.html +++ b/docs/articles/website_optimization.html @@ -32,7 +32,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -130,7 +130,7 @@

    Demo: Replication of John Myles White, Bandit Algorithms for Website Optimization

    Robin van Emden

    -

    2019-03-06

    +

    2019-03-17

    Source: vignettes/website_optimization.Rmd @@ -149,115 +149,115 @@

    m = max(x) return x.index(m)

    This introduces a bias that adds up over time, changing simulations’ results and plots. In R, (which uses 1 based indexing) this corresponds to always doing:

    - +

    Contextual correctly returns the index of one of the tied maxima random, fixing the bias, resulting in slightly different plots. In Python, a patch along the following lines ought to resolve this issue:

    def ind_max(x):
   max_value = max(x)
   max_keys = [k for k, v in enumerate(x) if v == max_value]
   return random.choice(max_keys)

    In R, this corresponds to:

    - +

    To illustrate, a replication of the original Figure 4-3 when running a simulation with the biased arm selection, (as used in the book) on the left, contextual’s unbiased simulation to the right:

    Chapter 4 - Debugging and epsilon greedy

    - +

    Figure 4-2. How often does the epsilon greedy algorithm select the best arm?

    -
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))

    Figure 4-3. How much reward does the epsilon greedy algorithm earn on average?

    -
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))

    Figure 4-4. How much reward has the epsilon greedy algorithm earned by trial t?

    -
    plot(history, type = "cumulative", regret = FALSE)
    +
    plot(history, type = "cumulative", regret = FALSE)

    Chapter 5 - Softmax

    - +

    Figure 5-2. How often does the softmax algorithm select the best arm?

    -
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))

    Figure 5-3. How much reward does the softmax algorithm earn on average?

    -
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))

    Figure 5-4. How much reward has the softmax algorithm earned by trial t?

    -
    plot(history, type = "cumulative", regret = FALSE)
    +
    plot(history, type = "cumulative", regret = FALSE)

    Chapter 6 - UCB

    - +

    Figure 6-3. How often does the UCB algorithm select the best arm?

    -
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "optimal", legend_position = "bottomright", ylim = c(0,1))

    Figure 6-4. How much reward does the UCB algorithm earn on average?

    -
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))
    +
    plot(history, type = "average", regret = FALSE, legend_position = "bottomright", ylim = c(0,1))

    Figure 6-5. How much reward has the UCB algorithm earned by trial t?

    -
    plot(history, type = "cumulative", regret = FALSE)
    +
    plot(history, type = "cumulative", regret = FALSE)

    @@ -284,7 +284,7 @@

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/authors.html b/docs/authors.html index 74a41b9..037a3ef 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -66,7 +66,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -187,7 +187,7 @@

    Authors

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/index.html b/docs/index.html index d0aa20f..2cb1ad7 100644 --- a/docs/index.html +++ b/docs/index.html @@ -35,7 +35,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -152,15 +152,15 @@

    Installation

    To install contextual from CRAN:

    -
    install.packages('contextual')
    +
    install.packages('contextual')

    To install the development version (requires the devtools package):

    -
    install.packages("devtools")
-devtools::install_github('Nth-iteration-labs/contextual')
    +
    install.packages("devtools")
+devtools::install_github('Nth-iteration-labs/contextual')

    When working on or extending the package, clone its GitHub repository, then do:

    -
    install.packages("devtools")
-devtools::install_deps(dependencies = TRUE)
-devtools::build()
-devtools::reload()
    +
    install.packages("devtools")
+devtools::install_deps(dependencies = TRUE)
+devtools::build()
+devtools::reload()

    clean and rebuild…

    @@ -330,7 +330,7 @@

    Dev status

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/news/index.html b/docs/news/index.html index 1d5b146..3d5bf63 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -66,7 +66,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -166,9 +166,17 @@

    Changelog

    Source: NEWS.md -
    +

    -contextual 0.9.8 2019-02-10 +contextual 0.9.8.1 Unreleased +

    +
      +
    • Specified previous version of set.seed sampler with RNGversion() calls
      • +
    +
    +
    +

    +contextual 0.9.8 2019-02-10

    • Major update
      • @@ -178,17 +186,17 @@

    • Additional demo scripts

    -
    +

    -contextual 0.9.1 2018-10-30 +contextual 0.9.1 2018-10-30

    • First CRAN release
    -
    +

    -contextual 0.9.0 Unreleased +contextual 0.9.0 Unreleased

    @@ -215,7 +224,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index c515aee..c5f4bc3 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,6 +1,6 @@ -pandoc: 2.1.3 -pkgdown: 1.3.0.9000 -pkgdown_sha: 4041eef8077af72e860a0144b945e463c55df118 +pandoc: '2.6' +pkgdown: 1.3.0 +pkgdown_sha: ~ articles: cmabs: cmabs.html cmabsoffline: cmabsoffline.html diff --git a/docs/reference/Agent.html b/docs/reference/Agent.html index 503eb9e..e916e18 100644 --- a/docs/reference/Agent.html +++ b/docs/reference/Agent.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1
    @@ -272,7 +272,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/Bandit.html b/docs/reference/Bandit.html index 3709f46..ed39c79 100644 --- a/docs/reference/Bandit.html +++ b/docs/reference/Bandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -260,7 +260,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/BasicBernoulliBandit.html b/docs/reference/BasicBernoulliBandit.html index 3f318a5..b5c998e 100644 --- a/docs/reference/BasicBernoulliBandit.html +++ b/docs/reference/BasicBernoulliBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -274,7 +274,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/BasicGaussianBandit.html b/docs/reference/BasicGaussianBandit.html index a2a551f..fafc874 100644 --- a/docs/reference/BasicGaussianBandit.html +++ b/docs/reference/BasicGaussianBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -274,7 +274,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/BootstrapTSPolicy.html b/docs/reference/BootstrapTSPolicy.html index 2e96b28..f908a1b 100644 --- a/docs/reference/BootstrapTSPolicy.html +++ b/docs/reference/BootstrapTSPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -257,7 +257,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualBernoulliBandit.html b/docs/reference/ContextualBernoulliBandit.html index 256aee9..3a11e1c 100644 --- a/docs/reference/ContextualBernoulliBandit.html +++ b/docs/reference/ContextualBernoulliBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -266,7 +266,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualBinaryBandit.html b/docs/reference/ContextualBinaryBandit.html index 940ebe1..f838e41 100644 --- a/docs/reference/ContextualBinaryBandit.html +++ b/docs/reference/ContextualBinaryBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -266,7 +266,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualEpochGreedyPolicy.html b/docs/reference/ContextualEpochGreedyPolicy.html index 10f5447..a6093ae 100644 --- a/docs/reference/ContextualEpochGreedyPolicy.html +++ b/docs/reference/ContextualEpochGreedyPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -212,7 +212,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualEpsilonGreedyPolicy.html b/docs/reference/ContextualEpsilonGreedyPolicy.html index ca34884..851bf9f 100644 --- a/docs/reference/ContextualEpsilonGreedyPolicy.html +++ b/docs/reference/ContextualEpsilonGreedyPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -255,7 +255,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualHybridBandit.html b/docs/reference/ContextualHybridBandit.html index f4b7700..2554f50 100644 --- a/docs/reference/ContextualHybridBandit.html +++ b/docs/reference/ContextualHybridBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -281,7 +281,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualLinTSPolicy.html b/docs/reference/ContextualLinTSPolicy.html index f7b3383..0f64e3e 100644 --- a/docs/reference/ContextualLinTSPolicy.html +++ b/docs/reference/ContextualLinTSPolicy.html @@ -73,7 +73,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -281,7 +281,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualLinearBandit.html b/docs/reference/ContextualLinearBandit.html index 4ec4e7c..118b72f 100644 --- a/docs/reference/ContextualLinearBandit.html +++ b/docs/reference/ContextualLinearBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -287,7 +287,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualLogitBTSPolicy.html b/docs/reference/ContextualLogitBTSPolicy.html index 63bd925..54455c9 100644 --- a/docs/reference/ContextualLogitBTSPolicy.html +++ b/docs/reference/ContextualLogitBTSPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -212,7 +212,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualLogitBandit.html b/docs/reference/ContextualLogitBandit.html index 3734f7f..7714e08 100644 --- a/docs/reference/ContextualLogitBandit.html +++ b/docs/reference/ContextualLogitBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -282,7 +282,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualPrecachingBandit.html b/docs/reference/ContextualPrecachingBandit.html index 3a8ac84..c800471 100644 --- a/docs/reference/ContextualPrecachingBandit.html +++ b/docs/reference/ContextualPrecachingBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -289,7 +289,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualTSProbitPolicy.html b/docs/reference/ContextualTSProbitPolicy.html index b8b9688..f2af37c 100644 --- a/docs/reference/ContextualTSProbitPolicy.html +++ b/docs/reference/ContextualTSProbitPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -212,7 +212,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContextualWheelBandit.html b/docs/reference/ContextualWheelBandit.html index 523e496..0845859 100644 --- a/docs/reference/ContextualWheelBandit.html +++ b/docs/reference/ContextualWheelBandit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -297,7 +297,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ContinuumBandit.html b/docs/reference/ContinuumBandit.html index e63ae2f..200a764 100644 --- a/docs/reference/ContinuumBandit.html +++ b/docs/reference/ContinuumBandit.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -281,7 +281,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/EpsilonFirstPolicy-1.png b/docs/reference/EpsilonFirstPolicy-1.png index 50ac3c53d7372648c20fe0be52336733be3809fe..36e2d3a07395a1bf874602f298b83162a09c7d5c 100644 GIT binary patch delta 399 zcmYk0u}y?A422C7AjWV+aSd!i0d_%i#r1Ru2~pS*3m~zwZ1s33T1NP3X`z1nd1ldrU=>BRf@!&=W`_Sy6 zgbflmL@XqYkp!8MwNK%Gc{JT}_GGXAQlAQ=aOY8$Osom%LWbnj0m?(w)l;*K!5B>% zTG8_|3rn+XpSDeBa2~Gg=aOf7mP=I#hEP}|(WR8g_K2LZMQk&5q;tBiN>)~#UY}1N x@6%|e%(R&?H=A4gEaytC^y+ANt$5vjKivVq+sniKV{iZI>*wO|dv$qz^9K|R&U^p> delta 399 zcmYj~u}uU)3`GqUAS6TwWCVnsA_ySA0LjkC5E3G|fC6lZ4z2-$lidXk*o|B=Ydjb6 z_2x^f`ET~HJM8pfj{pOJ02mMf2~c1R7z{&!1-RRQy?5(=g^(LTHk2mXU&aa#Zgj8@ z&3=@yLE?spg`_c(ATzS=x##}#Xxei2WG_JwZcw=QC@Ut`gxHh}$*BXBhpMZmW*LJq znl!Yg=VKO@X4yS$o6g`oT-nc(XL^?Jt3oh@!WxN|QX;z}a>f?1&D4?3>AIAxtUA5F zp1wY((M*|XGh=Qxx9(Zam0Ic5)ACyLy1Bjk1%QvYr^o01{Fm>aiXlVkhNi+*-))~hufT*m_p6uh@)!zH- z{SP_tLSayZA(q*lV`3o0x@1Upt)#UolQNoBT^*z*7@xmQU%n4xGA<^d%{GD+mS&0W zHg#umuCDyxdZy>_F+vKS8U`c`PDDziMdGK&WHCidJ+-EDx~4UMh z;sQfEK*C*U&UfgCZ=Ss841L<$lf~`HLSHQrpaBp710o;+3bY1|p((HcR~xX`90JWF za|pQ*WJ4*UR?N~IZd_<%Z<@829yLNDM&fEADU2k@VoBEN`V-gvR+Ou(&YtXpZ;s#R z5Cq`@g-gWQonvA}h;_-3?AkzEQwHT~R(16vHH-1}*Yxf8Fa~2ZDQLDUOAAZ0tnM~- zXK-$={NMFV&*5W)U`$`N~A^Br^jS5MNB=lrE|Kbms+Q*M=hwzG5(&P{ku5p zMm?pc^^86}w?5U=hx14s>5r3jvF69;Cx=^Kt`>h*H}Ul7^83o&v(^2V@7`Q~+}M4w X{`CIh=74{!LFM)C-p contextual - 0.9.8 + 0.9.8.1 @@ -255,7 +255,7 @@

    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.450
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.554
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

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    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.352
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.532
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    @@ -284,7 +284,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

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    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.326
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.451
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    @@ -277,7 +277,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/FixedPolicy.html b/docs/reference/FixedPolicy.html index ee2f005..685ba57 100644 --- a/docs/reference/FixedPolicy.html +++ b/docs/reference/FixedPolicy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -245,7 +245,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/GittinsBrezziLaiPolicy.html b/docs/reference/GittinsBrezziLaiPolicy.html index a6a904f..92c3e81 100644 --- a/docs/reference/GittinsBrezziLaiPolicy.html +++ b/docs/reference/GittinsBrezziLaiPolicy.html @@ -70,7 +70,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -276,7 +276,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

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0.9.8.1 @@ -241,7 +241,7 @@

    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.275
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.358
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    @@ -271,7 +271,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/History.html b/docs/reference/History.html index e46d4a6..57f025a 100644 --- a/docs/reference/History.html +++ b/docs/reference/History.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -309,7 +309,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/LifPolicy.html b/docs/reference/LifPolicy.html index cf5ad65..c2c02d9 100644 --- a/docs/reference/LifPolicy.html +++ b/docs/reference/LifPolicy.html @@ -79,7 +79,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -255,7 +255,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/LinUCBDisjointOptimizedPolicy.html b/docs/reference/LinUCBDisjointOptimizedPolicy.html index c5e56fa..8e8b6ef 100644 --- a/docs/reference/LinUCBDisjointOptimizedPolicy.html +++ b/docs/reference/LinUCBDisjointOptimizedPolicy.html @@ -73,7 +73,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -274,7 +274,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/LinUCBDisjointPolicy.html b/docs/reference/LinUCBDisjointPolicy.html index 21b82d5..a5da38d 100644 --- a/docs/reference/LinUCBDisjointPolicy.html +++ b/docs/reference/LinUCBDisjointPolicy.html @@ -73,7 +73,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -274,7 +274,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/LinUCBGeneralPolicy.html b/docs/reference/LinUCBGeneralPolicy.html index 956f2e6..e076b8a 100644 --- a/docs/reference/LinUCBGeneralPolicy.html +++ b/docs/reference/LinUCBGeneralPolicy.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -275,7 +275,7 @@

    Contents

    -

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    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:01.856
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.325
    #> Computing statistics.
    plot(history, type = "arms")
    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/Simulator.html b/docs/reference/Simulator.html index 8ae61d7..2932eb3 100644 --- a/docs/reference/Simulator.html +++ b/docs/reference/Simulator.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -311,7 +311,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/SoftmaxPolicy-1.png b/docs/reference/SoftmaxPolicy-1.png index 374687eb725aff5827f85061d3828df2cdd216d0..9f7d3b04e04c2e8a478aa059be995a9b2ce993da 100644 GIT binary patch delta 417 zcmW-bAyP##3`GM1#|~IQDi{QgH6S2SI6RKQAd&%zVTM&CmKCrA{v?aR^p*R5=JcB8 z^!D(0c>KIFCK^OSq{K`t#71M#P#R8Zq(Pck+AsGJW@8mrWUzsPzZ?7LP~byzc;iuF zz@k7zO$>xsNrVJ)nxc6Ch_0UMtqB%BW~fp!MM7lTCoDi2%r5KcgIvLI_@17iy}=5l zP!0pKYsV8&(GiWDvCTw5>PSavXRlnVjLW0~SYf@b8d=q|wyJHmk529M&ZE?r1r^b2 z{k=T>y}!*3~O5z*W8-R=F?&&l)G@5$Ns_36ds EKiU=34gdfE delta 417 zcmW-aF-`+P3`HFZI&Q!nA_@x6At<1vi!|<_ifAYz!2xV3M?rR<8<2*=zDSzc;cu+B zzuEuhpLge-Jsg;*5p^OVX5vn))EYIRW+Y1DB!SZUbG^>2ES&}EtRUg9#(L5OSd(a0 zc(gO%E}(bOuE4uyckhlI2f=a!5KSz^N&-w}QcMY{AR)4@=jtHUhgND0Yh(hN!MCsg zWd)`Sxv(qft9Jd|)62b(!& Iyt&{01Br{`Q~&?~ diff --git a/docs/reference/SoftmaxPolicy-2.png b/docs/reference/SoftmaxPolicy-2.png index a8282d6e85a826e751892bd7e0aa64e9924c389a..58fd11455bdf2b900d130009e99a4d3f113d7451 100644 GIT binary patch delta 465 zcmW-bF>BO85XC3qS}RitLAb(Vw+iA1NQi}vSnO0<*d*08Hiz8|*Cgo_K?DQZ9kWE6 z`v}^EkZMNj5b!Hp5!wId{qOPP?ZUn{v+LP<_F+#FQ6?%xOes++l!S7o%#@W_h>f@+ zl&FmFqe@~Ri7g3m^vA|1&I~kj%^Db5HnoyU;ZztdMSvCYVxS3Qa|S3XYh?|tpdbA? zIsSY4E;@dQkZ=-4H;wgCCI(zEB3zoVfu?=B_ zg;~Ix4XrX&&QLHz5X2YqLV^a{kPtKp0Gm|OKs74oI6Xi>WfmZYt!X)(>7Z@{&X zAVBPzQh}>|g66(szD|CbyX0neZ@pYE?bV8j3Q;8zVkWM{N~KT{Dn_CtPSOx!s`LA- z$^w+dSwWybH)cr@U`1N7#L#+Qt6Zya6}VOfUNx$NzN)|W1ts(j=l{Sa$#3c=QgzR@N`dj_o+9b zCZ!oZkS#|WBa}mHIM8sUBT^$h5|GfzCHi^@aEa#_~YKs^WEpyPoDmG Uah0$C>K}sMZoS+5^5*^Se-nZL-~a#s diff --git a/docs/reference/SoftmaxPolicy.html b/docs/reference/SoftmaxPolicy.html index 346cebc..afd8a3a 100644 --- a/docs/reference/SoftmaxPolicy.html +++ b/docs/reference/SoftmaxPolicy.html @@ -72,7 +72,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -247,7 +247,7 @@

    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.167
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.440
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    @@ -277,7 +277,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ThompsonSamplingPolicy-1.png b/docs/reference/ThompsonSamplingPolicy-1.png index 090d24bc3fa2090da023314c4665c91e81029282..4246c37632308b16e383855460e1289f4ce0929d 100644 GIT binary patch delta 432 zcmXAjF;0Uq3`SiRE`c~eGF4*a0xU>Sd*%XVLkNk%mKa!(dJ22xB*;DhTd&Y1fB61l zy?hzsXXm&-?!UI$h&mAy3AILzsVVhNU8oz0k|3QV(6_#?#jR-*Zi4itATeT<){-v3 zxKy8rI1K zbc1hU0m=$Y7jkK?fLHB&+|$dw(jogYLMWt%0r_{MDr&}@sV$Y$fhN4tEM#VlTr!tY z)+?mKD$Y`&CR9Ytd3t?5eY_9nQ98;;QScVZX%=l1FLfrvg|9`ARD QpUvChcXRoDcX5652Pm`I#Q*>R delta 432 zcmXAiF;0Uq424}5E`hiM5{q*Kgv0<#FAz^AHK|3o*e6dPvqzSMl z(af3^zU~aT3+P?6EAXz_-S^#b4Z;2f;F?&7l?0f|q}V2;f`-Vt#??Wp53ST1*2n}j zgKuF0$_h*ua$#4{SM7Y<)62cm_ceSOAr#WWfc(2r6*XhdR8H;bKoeeR7CN&=E}6?H zYZX#q6=$iC2^Cdyo?f3%AMeBaC>`aaax6X;^q3*Du54DEC$S6j^L~5$A)?Qh$A_oG Q_vY>JySe contextual - 0.9.8 + 0.9.8.1 @@ -250,7 +250,7 @@

    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.565
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.754
    #> Computing statistics.
    plot(history, type = "cumulative")
    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/UCB1Policy.html b/docs/reference/UCB1Policy.html index 366347f..2c084e7 100644 --- a/docs/reference/UCB1Policy.html +++ b/docs/reference/UCB1Policy.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -270,7 +270,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

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    Examp bandit <- BasicBernoulliBandit$new(weights = weights) agent <- Agent$new(policy, bandit) -history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:02.248
    #> Computing statistics.
    +history <- Simulator$new(agent, horizon, simulations, do_parallel = FALSE)$run()
    #> Simulation horizon: 100
    #> Number of simulations: 100
    #> Number of batches: 1
    #> Starting main loop.
    #> Finished main loop.
    #> Completed simulation in 0:00:01.968
    #> Computing statistics.
    plot(history, type = "cumulative")
    plot(history, type = "arms")
    @@ -275,7 +275,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

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    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/data_table_factors_to_numeric.html b/docs/reference/data_table_factors_to_numeric.html index 1d5e187..c5a5f53 100644 --- a/docs/reference/data_table_factors_to_numeric.html +++ b/docs/reference/data_table_factors_to_numeric.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -210,7 +210,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/dec-set.html b/docs/reference/dec-set.html index 86e9446..8af2cce 100644 --- a/docs/reference/dec-set.html +++ b/docs/reference/dec-set.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -215,7 +215,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/formatted_difftime.html b/docs/reference/formatted_difftime.html index 5e3cfc7..26b06e0 100644 --- a/docs/reference/formatted_difftime.html +++ b/docs/reference/formatted_difftime.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -210,7 +210,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/get_arm_context.html b/docs/reference/get_arm_context.html index 06e1b4f..9f37dd5 100644 --- a/docs/reference/get_arm_context.html +++ b/docs/reference/get_arm_context.html @@ -70,7 +70,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -228,7 +228,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/get_full_context.html b/docs/reference/get_full_context.html index 3c4ae3f..c0c031c 100644 --- a/docs/reference/get_full_context.html +++ b/docs/reference/get_full_context.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -226,7 +226,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/inc-set.html b/docs/reference/inc-set.html index 76d41f7..cbe589f 100644 --- a/docs/reference/inc-set.html +++ b/docs/reference/inc-set.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -215,7 +215,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ind.html b/docs/reference/ind.html index 9d9c182..9e92981 100644 --- a/docs/reference/ind.html +++ b/docs/reference/ind.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -210,7 +210,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/index.html b/docs/reference/index.html index 7d2efe3..87d786f 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -66,7 +66,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -679,7 +679,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/inv.html b/docs/reference/inv.html index ed6e8c1..b03a7c2 100644 --- a/docs/reference/inv.html +++ b/docs/reference/inv.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -212,7 +212,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/invgamma-1.png b/docs/reference/invgamma-1.png index 94cde492551f92d3b07515af893cb0d05feac13a..43373c41646837413be2f09f57b094a6afd58c82 100644 GIT binary patch delta 241 zcmXAhv1vmA3`F(810)-`7P!a^X+jDYu~gbqq`wscUct?Efh-b`*3rlJ?c;cGxb&YDVs;AZ&#x$lmU9)mlaXw#u)671;zmBKt>+*ix KFT1~3{ttH%Vsjb* delta 241 zcmXAfv28+O421n87GMJwNI~g3O)83n7CQeEq^C}GNQ?j*M7IYOg*}U(xChqhlg{7W zj<@4^dvdcdcXJUosJ^u2!iNIa6H3Nw8g8+;h~Y6r1Q@bpP;9ut9m6oh034ctppwv_ zn!`Ap@B contextual - 0.9.8 + 0.9.8.1 @@ -265,7 +265,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/invlogit.html b/docs/reference/invlogit.html index fbd7caa..25ce564 100644 --- a/docs/reference/invlogit.html +++ b/docs/reference/invlogit.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -210,7 +210,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/is_rstudio.html b/docs/reference/is_rstudio.html index 5dd6f7f..52f3222 100644 --- a/docs/reference/is_rstudio.html +++ b/docs/reference/is_rstudio.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -205,7 +205,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/mvrnorm.html b/docs/reference/mvrnorm.html index f4b140b..b4fc802 100644 --- a/docs/reference/mvrnorm.html +++ b/docs/reference/mvrnorm.html @@ -70,7 +70,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -221,7 +221,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/one_hot.html b/docs/reference/one_hot.html index 52091c4..b7b4c23 100644 --- a/docs/reference/one_hot.html +++ b/docs/reference/one_hot.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -267,7 +267,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/ones_in_zeroes.html b/docs/reference/ones_in_zeroes.html index 60b80a6..bc2dc5a 100644 --- a/docs/reference/ones_in_zeroes.html +++ b/docs/reference/ones_in_zeroes.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -214,7 +214,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/plot.history.html b/docs/reference/plot.history.html index af93968..1ef8d45 100644 --- a/docs/reference/plot.history.html +++ b/docs/reference/plot.history.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -218,7 +218,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/print.history.html b/docs/reference/print.history.html index a8c2ab0..cc6b633 100644 --- a/docs/reference/print.history.html +++ b/docs/reference/print.history.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -218,7 +218,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/prob_winner.html b/docs/reference/prob_winner.html index 802b910..dfb2575 100644 --- a/docs/reference/prob_winner.html +++ b/docs/reference/prob_winner.html @@ -70,7 +70,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -222,7 +222,7 @@

    Author

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/sample_one_of.html b/docs/reference/sample_one_of.html index 206ab38..d83ccc7 100644 --- a/docs/reference/sample_one_of.html +++ b/docs/reference/sample_one_of.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -210,7 +210,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/set_external.html b/docs/reference/set_external.html index 1f09570..609cc02 100644 --- a/docs/reference/set_external.html +++ b/docs/reference/set_external.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -236,7 +236,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/sherman_morrisson.html b/docs/reference/sherman_morrisson.html index 4fef75d..9a2f91b 100644 --- a/docs/reference/sherman_morrisson.html +++ b/docs/reference/sherman_morrisson.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -208,7 +208,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/sim_post.html b/docs/reference/sim_post.html index 322406b..a0fe63f 100644 --- a/docs/reference/sim_post.html +++ b/docs/reference/sim_post.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -239,7 +239,7 @@

    Author

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/sum_of.html b/docs/reference/sum_of.html index 0de54b6..ec5bd9e 100644 --- a/docs/reference/sum_of.html +++ b/docs/reference/sum_of.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -219,7 +219,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/summary.history.html b/docs/reference/summary.history.html index d9a3457..d04b5d1 100644 --- a/docs/reference/summary.history.html +++ b/docs/reference/summary.history.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -219,7 +219,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/value_remaining-1.png b/docs/reference/value_remaining-1.png index 3ab3d380608a01cbaccb437a9a5954a8f94809af..900c702487426a9299eb74bb5843e572d135839b 100644 GIT binary patch delta 234 zcmW-Z!3jb^3`AoC-mF2$%{IJ!NUpz?sX(xeIopE`B<*Bz*5NTEdCR_z*YSS9&BENx z)v%;?E&H$&o&v5rM1@|vkcdc&^hgZ|Fk~r4U&0+J0x~-UY8MF>S`5>eeiBZ^U&XdN q#U@)lTvPBu6a{L#szx=dHB2qmnqf?1n$tClv($4wZ{N@Lg8L7MKy`co delta 234 zcmW-X!3_dX2t#oJ*YNC-DU1tvgAF`8fvLNgj^NP+U>1Jtw|QxR$MgEUzRnLf3v)MD z!;;#y?88oY3b^hN75a7|5s?<@ks1(S$Wjd4;EoglnH>VPiv$ZThG|T{5l+Nk#kM=e qCR;sRQ}99*1!}vhMm4K7OfA-$VN7G1(>05;)bqW3?(gH_aryyQ5P!e` diff --git a/docs/reference/value_remaining.html b/docs/reference/value_remaining.html index d0140dc..9bef1f1 100644 --- a/docs/reference/value_remaining.html +++ b/docs/reference/value_remaining.html @@ -70,7 +70,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -241,7 +241,7 @@

    Author

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/var_welford.html b/docs/reference/var_welford.html index f62af31..3911c1f 100644 --- a/docs/reference/var_welford.html +++ b/docs/reference/var_welford.html @@ -71,7 +71,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -214,7 +214,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/which_max_list.html b/docs/reference/which_max_list.html index a51af2f..5e5725d 100644 --- a/docs/reference/which_max_list.html +++ b/docs/reference/which_max_list.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -224,7 +224,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/docs/reference/which_max_tied.html b/docs/reference/which_max_tied.html index abb98e4..d106770 100644 --- a/docs/reference/which_max_tied.html +++ b/docs/reference/which_max_tied.html @@ -69,7 +69,7 @@ contextual - 0.9.8 + 0.9.8.1 @@ -216,7 +216,7 @@

    Contents

    -

    Site built with pkgdown 1.3.0.9000.

    +

    Site built with pkgdown 1.3.0.

    diff --git a/vignettes/only_pkgdown/faq.Rmd b/vignettes/only_pkgdown/faq.Rmd index 7fb25ba..e1a9940 100644 --- a/vignettes/only_pkgdown/faq.Rmd +++ b/vignettes/only_pkgdown/faq.Rmd @@ -3,10 +3,6 @@ title: "Development FAQ" author: "Robin van Emden" date: "`r Sys.Date()`" output: rmarkdown::html_vignette -vignette: > - %\VignetteIndexEntry{Frequently Asked Questions} - %\VignetteEngine{knitr::rmarkdown} - %\VignetteEncoding{UTF-8} --- ```{r setup, include = FALSE, cache = TRUE}