This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
-
Updated
Feb 15, 2022 - Python
This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
ORLA is a symbolic reinforcement learning approach that learns a value-based argumentation framework as a reasoning engine for solving a task. This repo demonstrates ORLA on both the Foggy Frozen Lake and the Takeaway tasks.
We use Policy Iteration and Value Iteration to solve the frozen lake problem
Various reinforcement learning algorithms implemented on the frozen lake grid world.
End-to-end reinforcement learning pipeline integrating abstract argumentation
Using the cross-entropy method to solve Frozen Lake.
Add a description, image, and links to the frozen-lake topic page so that developers can more easily learn about it.
To associate your repository with the frozen-lake topic, visit your repo's landing page and select "manage topics."