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actions.py
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actions.py
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from parse_en import *
from nl_to_fol import *
import sys
sys.path.insert(0, "../logic")
from logic.logic import *
from phidias.Types import *
import configparser
import math
from datetime import datetime
from difflib import SequenceMatcher
import pyttsx3
import winsound
config = configparser.ConfigParser()
config.read('config.ini')
cnt = itertools.count(1)
dav = itertools.count(1)
VERBOSE = config.getboolean('NL_TO_FOL', 'VERBOSE')
LANGUAGE = config.get('NL_TO_FOL', 'LANGUAGE')
ASSIGN_RULES_ADMITTED = config.getboolean('NL_TO_FOL', 'ASSIGN_RULES_ADMITTED')
WAIT_TIME = config.getint('AGENT', 'WAIT_TIME')
LOG_ACTIVE = config.getboolean('AGENT', 'LOG_ACTIVE')
INCLUDE_ACT_POS = config.getboolean('POS', 'INCLUDE_ACT_POS')
INCLUDE_NOUNS_POS = config.getboolean('POS', 'INCLUDE_NOUNS_POS')
INCLUDE_ADJ_POS = config.getboolean('POS', 'INCLUDE_ADJ_POS')
INCLUDE_PRP_POS = config.getboolean('POS', 'INCLUDE_PRP_POS')
INCLUDE_ADV_POS = config.getboolean('POS', 'INCLUDE_ADV_POS')
OBJ_JJ_TO_NOUN = config.getboolean('POS', 'OBJ_JJ_TO_NOUN')
GEN_PREP = config.getboolean('GEN', 'GEN_PREP')
GEN_ADJ = config.getboolean('GEN', 'GEN_ADJ')
GEN_ADV = config.getboolean('GEN', 'GEN_ADV')
GEN_EXTRA = config.getboolean('GEN', 'GEN_EXTRA')
GEN_EXTRA_POS = config.get('GEN', 'EXTRA_GEN_POS').split(", ")
parser = Parse(VERBOSE)
m = ManageFols(VERBOSE, LANGUAGE)
# Clauses Knowledge Base instantion
kb_fol = FolKB([])
# FOl Reasoning procedures
class aggr_adj(Procedure): pass
class aggr_adv(Procedure): pass
class aggr_nouns(Procedure): pass
class mod_to_gnd(Procedure): pass
class gnd_prep_obj(Procedure): pass
class prep_to_gnd(Procedure): pass
class finalize_clause(Procedure): pass
class parse(Procedure): pass
class process_clause(Procedure): pass
class finalize_gnd(Procedure): pass
class apply_adv(Procedure): pass
class actions_to_clauses(Procedure): pass
class gnd_actions(Procedure): pass
class new_def_clause(Procedure): pass
class process_rule(Procedure): pass
# Reactive procedures - direct commands
class parse_command(Procedure): pass
class aggr_entities(Procedure): pass
class produce_intent(Procedure): pass
class produce_mod(Procedure): pass
# Reactive procedures - routines
class parse_routine(Procedure): pass
class produce_conds(Procedure): pass
class aggr_ent_conds(Procedure): pass
class produce_mod_conds(Procedure): pass
class produce_routine(Procedure): pass
class aggr_ent_rt(Procedure): pass
class produce_mod_rt(Procedure): pass
# check for routines execution
class check_conds(Procedure): pass
# start agent command
class go(Procedure): pass
# STT Front-End procedures
class s(Procedure): pass
# initialize Clauses Kb
class c(Procedure): pass
# mode reactors
class HOTWORD_DETECTED(Reactor): pass
class STT(Reactor): pass
class WAKE(Belief): pass
class LISTEN(Belief): pass
class REASON(Belief): pass
class RETRACT(Belief): pass
class IS_RULE(Belief): pass
class WAIT(Belief): pass
class ANSWER(Reactor): pass
# domotic reactive routines
class r1(Procedure): pass
class r2(Procedure): pass
# domotic direct commands
class d1(Procedure): pass
class d2(Procedure): pass
# domotic sensor simulatons
class s1(Procedure): pass
class s2(Procedure): pass
# Fol reasoning utterances
class c1(Procedure): pass
class c2(Procedure): pass
class c3(Procedure): pass
class c4(Procedure): pass
class c5(Procedure): pass
class c6(Procedure): pass
# Fol query utterance
class q(Procedure): pass
# normal requests beliefs
class GROUND(Belief): pass
class PRE_MOD(Belief): pass
class MOD(Belief): pass
class PRE_INTENT(Belief): pass
class INTENT(Reactor): pass
# routines beliefs
class PRE_ROUTINE(Belief): pass
class ROUTINE(Belief): pass
class ROUTINE_PRE_MOD(Belief): pass
class ROUTINE_MOD(Belief): pass
class ROUTINE_GROUND(Belief): pass
# conditionals beliefs
class PRE_COND(Belief): pass
class COND(Belief): pass
class COND_GROUND(Belief): pass
class COND_PRE_MOD(Belief): pass
class SENSOR(Belief): pass
class START_ROUTINE(Reactor): pass
# clause
class CLAUSE(Belief): pass
# action
class ACTION(Belief): pass
# preposition
class PREP(Belief): pass
# ground
class GND(Belief): pass
# adverb
class ADV(Belief): pass
# adjective
class ADJ(Belief): pass
# left clause
class LEFT_CLAUSE(Belief): pass
# definite clause
class DEF_CLAUSE(Belief): pass
# remain
class REMAIN(Belief): pass
# preposition accumlator
class PRE_CROSS(Belief): pass
# Modificators number
class GEN_MASK(Belief): pass
# Actions crossing var
class ACT_CROSS_VAR(Belief): pass
# parse rule beliefs
class DEP(Belief): pass
class MST_ACT(Belief): pass
class MST_VAR(Belief): pass
class MST_PREP(Belief): pass
class MST_BIND(Belief): pass
class MST_COMP(Belief): pass
class MST_COND(Belief): pass
class parse_deps(Procedure): pass
class feed_mst(Procedure): pass
class PROCESS_STORED_MST(Reactor): pass
class log(Action):
"""log direct assertions from keyboard"""
def execute(self, *args):
a = str(args).split("'")
if LOG_ACTIVE:
with open("log.txt", "a") as myfile:
myfile.write("\n"+a[1]+": "+a[5])
class beep(Action):
"""plays a beep"""
def execute(self):
winsound.PlaySound('ding.wav', winsound.SND_FILENAME)
class say(Action):
"""Text-to-Speech"""
def execute(self, *args):
text = args[0]()
# setting TTS engine
engine = pyttsx3.init()
voices = engine.getProperty('voices')
engine.setProperty('voice', voices[2].id)
engine.setProperty('rate', 150)
engine.say(text)
engine.runAndWait()
class reset_ct(Action):
"""Reset execution time"""
def execute(self):
parser.set_start_time()
class show_ct(Action):
"""Show execution time"""
def execute(self):
ct = parser.get_comp_time()
print("\nExecution time: ", ct)
if LOG_ACTIVE:
with open("log.txt", "a") as myfile:
myfile.write("\nExecution time: "+str(ct))
class set_wait(Action):
"""Set duration of the session from WAIT_TIME in config.ini [AGENT]"""
def execute(self):
self.assert_belief(WAIT(WAIT_TIME))
if LOG_ACTIVE:
with open("log.txt", "a") as myfile:
myfile.write("\n\n------ NEW SESSION ------ "+str(datetime.now().strftime("%d/%m/%Y %H:%M:%S")))
class eval_cls(ActiveBelief):
"""ActiveBelief for Beliefs KB and Clauses KB interaction"""
def evaluate(self, arg1):
utterance = str(arg1).split("'")[1]
bc_result = kb_fol.ask(expr(utterance))
print("\n ---- NOMINAL REASONING ---\n")
print("Result: " + str(bc_result))
if bc_result is False:
print("\n\n ---- NESTED REASONING ---")
candidates = []
nested_result = kb_fol.nested_ask(expr(utterance), candidates)
print("Result: " + str(nested_result))
if nested_result is None:
return True
elif nested_result is False:
return False
else:
return True
else:
return True
class lemma_in_syn(ActiveBelief):
"""ActiveBelief for checking if a synset comprises a lemma"""
def evaluate(self, arg1, arg2):
verb = str(arg1).split("'")[3]
synset = str(arg2).split("'")[1]
pos = wordnet.VERB
syns = wordnet.synsets(verb, pos=pos, lang=LANGUAGE)
for syn in syns:
if syn.name() == synset:
return True
return False
class preprocess_clause(Action):
"""Producting beliefs to feed the Definite Clauses Builder"""
def execute(self, *args):
gen_mask = str(args[0]())
mode = str(args[1]())
type = str(args[2]())
print("\n--------- NEW GENERALIZATION ---------\n ")
print("gen_mask: " + gen_mask)
print("mode: " + mode)
print("type: " + type + "\n")
if mode == "ONE":
Gen_mode = False
else:
Gen_mode = True
self.MAIN_NEG_PRESENT = False
deps = parser.get_last_deps()
for i in range(len(deps)):
governor = self.get_lemma(deps[i][1]).capitalize() + ":" + self.get_pos(deps[i][1])
dependent = self.get_lemma(deps[i][2]).capitalize() + ":" + self.get_pos(deps[i][2])
deps[i] = [deps[i][0], governor, dependent]
print("\n" + str(deps))
MST = parser.get_last_MST()
print("\nMST: \n" + str(MST))
print("\nGMC_SUPP: \n" + str(parser.GMC_SUPP))
print("\nSUPP_SUPP_REV: \n" + str(parser.GMC_SUPP_REV))
print("\nLCD: \n" + str(parser.LCD))
# MST varlist correction on cases of adj-obj
if OBJ_JJ_TO_NOUN is True:
for v in MST[1]:
if self.get_pos(v[1]) in ['JJ', 'JJR', 'JJS']:
old_value = v[1]
new_value = self.get_lemma(v[1]) + ":NNP"
v[1] = new_value
new_value_clean = parser.get_lemma(new_value.lower())[:-2]
print("\nadj-obj correction...", new_value_clean)
# checking if the lemma has a disambiguation
if new_value_clean in parser.GMC_SUPP_REV:
parser.LCD[parser.GMC_SUPP_REV[new_value_clean]] = new_value_clean
# binds correction
for b in MST[3]:
if b[0] == old_value:
b[0] = new_value
vect_LR_fol = m.build_LR_fol(MST, 'e')
print("\nBefore dealing case:\n" + str(vect_LR_fol))
if len(vect_LR_fol) == 0:
print("\n --- IMPROPER VERBAL PHRASE COSTITUTION ---")
self.assert_belief(ANSWER("Improper verbal phrase"))
return
if type == "NOMINAL":
# NOMINAL CASE
CHECK_IMPLICATION = m.check_implication(vect_LR_fol)
if not CHECK_IMPLICATION:
if ASSIGN_RULES_ADMITTED:
check_isa = m.check_for_rule(deps, vect_LR_fol)
if check_isa:
self.assert_belief(IS_RULE("TRUE"))
dclause = vect_LR_fol[:]
else:
dclause = vect_LR_fol[:]
dclause[1] = ["==>"]
else:
# RULE CASE
ent_root = self.get_ent_ROOT(deps)
dav_rule = self.get_dav_rule(vect_LR_fol, ent_root)
positive_vect_LR_fol = []
for v in vect_LR_fol:
lemma = self.get_lemma(v[0])[:-2]
if self.check_neg(lemma, LANGUAGE) and v[1] == dav_rule:
self.assert_belief(RETRACT("ON"))
else:
positive_vect_LR_fol.append(v)
vect_LR_fol_plus_isa = m.build_isa_fol(positive_vect_LR_fol, deps)
dclause = m.isa_fol_to_clause(vect_LR_fol_plus_isa)
print("\nAfter dealing case:\n" + str(dclause))
# IMPLICATION CASES
if dclause[1][0] == "==>":
mods = []
for v in dclause[2]:
if self.get_pos(v[0]) in GEN_EXTRA_POS and GEN_EXTRA is True:
mods.append(v[0])
if self.get_pos(v[0]) == "IN" and GEN_PREP is True:
mods.append(v[0])
elif self.get_pos(v[0]) in ['JJ', 'JJR', 'JJS'] and GEN_ADJ is True:
mods.append(v[0])
elif self.get_pos(v[0]) in ['RB', 'RBR', 'RBS']:
if GEN_ADV is True:
mods.append(v[0])
lemma = self.get_lemma(v[0])[:-2]
if self.check_neg(lemma, LANGUAGE):
print("\nNot a definite clause!")
return
if gen_mask == "BASE":
print("\nmods: " + str(mods))
nmods = int(math.pow(2, len(mods))) - 1
print("\ngereralizations number: " + str(nmods) + "\n")
actual_mask = ""
for i in range(len(mods)):
actual_mask = actual_mask + "0"
gen_mask = actual_mask
# creating dictionary
voc = {}
for i in range(len(mods)):
if gen_mask[i] == '1':
val = True
else:
val = False
voc.update({mods[i]: val})
# triggering generalizations production
if len(mods) > 0 and Gen_mode is True:
inc_mask = self.get_inc_mask(actual_mask)
self.assert_belief(GEN_MASK(inc_mask))
elif gen_mask == "FULL":
# creating dictionary
voc = {}
for i in range(len(mods)):
voc.update({mods[i]: True})
else:
# creating dictionary
voc = {}
full_true_voc = {}
for i in range(len(mods)):
if gen_mask[i] == '1':
val = True
else:
val = False
voc.update({mods[i]: val})
full_true_voc.update({mods[i]: True})
inc_mask = self.get_inc_mask(gen_mask)
if len(inc_mask) == len(gen_mask):
self.assert_belief(GEN_MASK(inc_mask))
print("\nPROCESSING LEFT HAND-SIDE...")
self.process_fol(dclause[0], "LEFT", voc)
print("\nPROCESSING RIGHT HAND-SIDE...")
self.process_fol(dclause[2], "RIGHT", voc)
# FLAT CASES
else:
mods = []
nomain_negs = []
main_neg_index = 0
ent_root = self.get_ent_ROOT(deps)
dav_act = self.get_dav_rule(dclause, ent_root)
for v in dclause:
if self.get_pos(v[0]) in GEN_EXTRA_POS and GEN_EXTRA is True:
mods.append(v[0])
elif self.get_pos(v[0]) == "IN" and GEN_PREP is True:
mods.append(v[0])
elif (self.get_pos(v[0]) == "JJ" or self.get_pos(v[0]) == "JJS") and GEN_ADJ is True:
mods.append(v[0])
if self.get_pos(v[0]) in ['RB', 'RBR', 'RBS']:
lemma = self.get_lemma(v[0])[:-2]
if self.check_neg(lemma, LANGUAGE):
if v[1] == dav_act:
self.MAIN_NEG_PRESENT = True
self.assert_belief(RETRACT("ON"))
main_neg_index = len(mods) - 1
dclause.remove(v)
else:
if GEN_ADV is True:
mods.append(v[0])
nomain_negs.append(v)
else:
if GEN_ADV is True:
mods.append(v[0])
# every verb/adj will carry its non-main negative
negs = {}
for n in nomain_negs:
for v in dclause:
if v[1] == n[1]:
if v not in nomain_negs:
negs.update({v[0]: n[0]})
# only reason
if gen_mask == "FULL":
# creating dictionary
voc = {}
for i in range(len(mods)):
voc.update({mods[i]: True})
elif gen_mask == "BASE":
actual_mask = ""
if self.MAIN_NEG_PRESENT:
for i in range(len(mods)):
if i == main_neg_index:
actual_mask = actual_mask + "0"
else:
actual_mask = actual_mask + "1"
else:
for i in range(len(mods)):
actual_mask = actual_mask + "0"
gen_mask = actual_mask
# creating vocabolary
voc = {}
for i in range(len(mods)):
if gen_mask[i] == '1':
val = True
else:
val = False
voc.update({mods[i]: val})
# voc rectification for carrying negations, other negations = True
for nm in nomain_negs:
voc[nm[0]] = True
for ng in negs:
if ng in voc:
voc[negs[ng]] = voc[ng]
nmods = int(math.pow(2, len(mods))) - 1
print("\ngereralizations number: " + str(nmods))
# triggering generalizations production
if len(mods) > 0 and Gen_mode and not self.MAIN_NEG_PRESENT:
inc_mask = self.get_inc_mask(actual_mask)
self.assert_belief(GEN_MASK(inc_mask))
else:
# creating vocabolary
voc = {}
for i in range(len(mods)):
if gen_mask[i] == '1':
val = True
else:
val = False
voc.update({mods[i]: val})
# voc rectification for carrying negations, other negations = True
for nm in nomain_negs:
voc[nm[0]] = True
for ng in negs:
if ng in voc:
voc[negs[ng]] = voc[ng]
inc_mask = self.get_inc_mask(gen_mask)
if len(inc_mask) == len(gen_mask):
self.assert_belief(GEN_MASK(inc_mask))
self.process_fol(dclause, "FLAT", voc)
def get_ent_ROOT(self, deps):
for d in deps:
if d[0] == "ROOT":
return d[1]
def get_dav_rule(self, fol, ent_root):
for f in fol:
if f[0] == ent_root:
return f[1]
return False
def check_neg(self, word, language):
pos = wordnet.ADV
syns = wordnet.synsets(word, pos=pos, lang=language)
for synset in syns:
if str(synset.name()) in ['no.r.01', 'no.r.02', 'no.r.03', 'not.r.01']:
return True
return False
def get_inc_mask(self, n):
diff = str(bin(int(n, 2) + int("1", 2)))[2:]
delta = len(n) - len(diff)
for i in range(delta):
diff = "0" + diff
return diff
def get_dec_mask(self, n):
diff = str(bin(int(n, 2) - int("00001", 2)))[2:]
delta = len(n) - len(diff)
for i in range(delta):
diff = "0" + diff
return diff
def get_nocount_lemma(self, lemma):
lemma_nocount = ""
total_lemma = lemma.split("_")
for i in range(len(total_lemma)):
if i == 0:
lemma_nocount = total_lemma[i].split(':')[0][:-2] + ":" + total_lemma[i].split(':')[1]
else:
lemma_nocount = total_lemma[i].split(':')[0][:-2] + ":" + total_lemma[i].split(':')[1] + "_" + lemma_nocount
return lemma_nocount
def process_fol(self, vect_fol, id, voc):
print("\n------DICTIONARY------")
print(voc)
print("----------------------\n")
# actions-crossing var list
var_crossing = []
admissible_vars = ['x']
# prepositions
for v in vect_fol:
if len(v) == 3:
label = self.get_nocount_lemma(v[0])
if GEN_PREP is False or id == "LEFT":
if INCLUDE_PRP_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
self.assert_belief(PREP(str(id), v[1], lemma, v[2]))
print("PREP(" + str(id) + ", " + v[1] + ", " + lemma + ", " + v[2] + ")")
if v[1] not in admissible_vars:
admissible_vars.append(v[1])
if v[2] not in admissible_vars:
admissible_vars.append(v[2])
elif v[0] in voc and voc[v[0]] is True:
if INCLUDE_PRP_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
self.assert_belief(PREP(str(id), v[1], lemma, v[2]))
print("PREP(" + str(id) + ", " + v[1] + ", " + lemma + ", " + v[2] + ")")
if v[1] not in admissible_vars:
admissible_vars.append(v[1])
if v[2] not in admissible_vars:
admissible_vars.append(v[2])
# actions
for v in vect_fol:
ACTION_ASSERTED = False
if len(v) == 4:
label = self.get_nocount_lemma(v[0])
pos = self.get_pos(v[0])
if INCLUDE_ACT_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if GEN_EXTRA is True and pos in GEN_EXTRA_POS:
if (v[0] in voc and voc[v[0]] is True):
self.assert_belief(ACTION(str(id), lemma, v[1], v[2], v[3]))
print("ACTION(" + str(id) + ", " + lemma + ", " + v[1] + ", " + v[2] + ", " + v[3] + ")")
ACTION_ASSERTED = True
else:
self.assert_belief(ACTION(str(id), lemma, v[1], v[2], v[3]))
print("ACTION(" + str(id) + ", " + lemma + ", " + v[1] + ", " + v[2] + ", " + v[3] + ")")
ACTION_ASSERTED = True
if ACTION_ASSERTED:
# check for var action crossing
if v[2] in var_crossing:
self.assert_belief(ACT_CROSS_VAR(str(id), v[2], lemma))
print("ACT_CROSS_VAR(" + str(id) + ")")
else:
if v[2] != "__":
var_crossing.append(v[2])
if v[3] in var_crossing:
self.assert_belief(ACT_CROSS_VAR(str(id), v[3], lemma))
print("ACT_CROSS_VAR(" + str(id) + ")")
else:
if v[3] != "__":
var_crossing.append(v[3])
if v[1] not in admissible_vars:
admissible_vars.append(v[1])
if v[2] not in admissible_vars:
admissible_vars.append(v[2])
if v[3] not in admissible_vars:
admissible_vars.append(v[3])
# nouns
for v in vect_fol:
if len(v) == 2:
if self.get_pos(v[0]) in ['NNP', 'NNPS', 'PRP', 'CD', 'NN', 'NNS', 'PRP', 'PRP$']:
label = self.get_nocount_lemma(v[0])
if INCLUDE_NOUNS_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if v[1] in admissible_vars:
self.assert_belief(GND(str(id), v[1], lemma))
print("GND(" + str(id) + ", " + v[1] + ", " + lemma + ")")
# adjectives, adverbs
for v in vect_fol:
if self.get_pos(v[0]) in ['JJ', 'JJR', 'JJS']:
label = self.get_nocount_lemma(v[0])
if GEN_ADJ is False or id == "LEFT":
if INCLUDE_ADJ_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if v[1] in admissible_vars:
self.assert_belief(ADJ(str(id), v[1], lemma))
print("ADJ(" + str(id) + ", " + v[1] + ", " + lemma + ")")
elif v[0] in voc and voc[v[0]] is True:
if INCLUDE_ADJ_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if v[1] in admissible_vars:
self.assert_belief(ADJ(str(id), v[1], lemma))
print("ADJ(" + str(id) + ", " + v[1] + ", " + lemma + ")")
elif self.get_pos(v[0]) in ['RB', 'RBR', 'RBS', 'RP']:
label = self.get_nocount_lemma(v[0])
if GEN_ADV is False or id == "LEFT":
if INCLUDE_ADV_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if v[1] in admissible_vars:
self.assert_belief(ADV(str(id), v[1], lemma))
print("ADV(" + str(id) + ", " + v[1] + ", " + lemma + ")")
elif v[0] in voc and voc[v[0]] is True:
if INCLUDE_ADV_POS:
lemma = label
else:
lemma = parser.get_lemma(label)
if v[1] in admissible_vars:
self.assert_belief(ADV(str(id), v[1], lemma))
print("ADV(" + str(id) + ", " + v[1] + ", " + lemma + ")")
def get_pos(self, s):
first = s.split('_')[0]
s_list = first.split(':')
if len(s_list) > 1:
return s_list[1]
else:
return s_list[0]
def get_lemma(self, s):
s_list = s.split(':')
return s_list[0]
class retract_clause(Action):
"""Retract a clause from the Clauses KB"""
def execute(self, *args):
sentence = args[0]()
mf = parser.morph(sentence)
print("\n" + mf)
def_clause = expr(mf)
if def_clause in kb_fol.clauses:
kb_fol.retract(def_clause)
class new_clause(Action):
"""Assert a clause in the Clauses KB"""
def execute(self, *args):
sentence = args[0]()
mf = parser.morph(sentence)
print("\n", mf)
def_clause = expr(mf)
kb_fol.nested_tell(def_clause)
class reason(Action):
"""Query the Clauses KB with Backward-Chaining, and if it fails with Nested Reasoning"""
def execute(self, *args):
definite_clause = args[0]()
q = parser.morph(definite_clause)
print("Query: " + q)
print("OCCUR_CHECK: ", exec_occur_check)
bc_result = kb_fol.ask(expr(q))
print("\n ---- NOMINAL REASONING ---\n")
print("Result: " + str(bc_result))
print("Backward-Chaining Query time: ", parser.get_comp_time())
if bc_result is not False:
self.assert_belief(ANSWER("True, by nominal reasoning"))
else:
print("\n\n ---- NESTED REASONING ---")
candidates = []
nested_result = kb_fol.nested_ask(expr(q), candidates)
print("\nResult: ", nested_result)
if nested_result is False:
self.assert_belief(ANSWER("False, by nominal and nested reasoning"))
else:
self.assert_belief(ANSWER("True, by nested reasoning"))
class assert_command(Action):
"""Producting beliefs to feed the Direct Command and Routine parsers"""
def execute(self, *args):
sentence = args[0]()
# ----> words or chars not dealing well with fol conversion
# verb_i2 must not be part of some verb_j1, with i!=j
# [verb_i1, verb_i2]
SWAP_STR = [["turn on", "change"], [":", "."], ["_", "-"]]
for s in SWAP_STR:
sentence = sentence.lower().replace(s[0], s[1])
print(sentence)
deps = parser.get_last_deps()
MST = parser.get_last_MST()
m = ManageFols(VERBOSE, LANGUAGE)
vect_LR_fol = m.build_LR_fol(MST, 'd')
# getting fol's type
check_isa = False
check_implication = m.check_implication(vect_LR_fol)
if check_implication is False:
check_isa = m.check_isa(vect_LR_fol, deps)
gentle_LR_fol = m.vect_LR_to_gentle_LR(vect_LR_fol, deps, check_implication, check_isa)
print(str(gentle_LR_fol))
if len(vect_LR_fol) > 0 and vect_LR_fol[1][0] == "==>":
dateTimeObj = datetime.now()
id_routine = dateTimeObj.microsecond
self.process_conditions(vect_LR_fol[0], id_routine)
self.process_routine(vect_LR_fol[2], id_routine)
else:
self.process(vect_LR_fol)
def process_conditions(self, vect_fol, id_routine):
dateTimeObj = datetime.datetime.now()
id_ground = dateTimeObj.microsecond
for g in vect_fol:
if len(g) == 3:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(COND_PRE_MOD(g[1], lemma, g[2]))
for g in vect_fol:
if len(g) == 2:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(COND_GROUND(str(id_ground), g[1], lemma))
id_ground = id_ground + 1
for g in vect_fol:
if len(g) == 4:
verb = self.get_verbs_nopos(g[0])
self.assert_belief(PRE_COND(str(id_routine), verb, g[1], g[2], g[3]))
def process_routine(self, vect_fol, id_routine):
dateTimeObj = datetime.datetime.now()
id_ground = dateTimeObj.microsecond
for g in vect_fol:
if len(g) == 3:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(ROUTINE_PRE_MOD(g[1], lemma, g[2]))
for g in vect_fol:
if len(g) == 2:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(ROUTINE_GROUND(str(id_ground), g[1], lemma))
id_ground = id_ground + 1
for g in vect_fol:
if len(g) == 4:
verb = self.get_verbs_nopos(g[0])
self.assert_belief(PRE_ROUTINE(str(id_routine), verb, g[1], g[3], "", ""))
def process(self, vect_fol):
dateTimeObj = datetime.now()
id_ground = dateTimeObj.microsecond
for g in vect_fol:
if len(g) == 3:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(PRE_MOD(g[1], lemma, g[2]))
if len(g) == 2:
lemma = self.get_lemma(g[0])[:-2]
self.assert_belief(GROUND(str(id_ground), g[1], lemma))
id_ground = id_ground + 1
if len(g) == 4:
verb = self.get_verbs_nopos(g[0])
self.assert_belief(PRE_INTENT(verb, g[1], g[3], "", ""))
def get_verbs_nopos(self, lemma):
lemma_nopos = ""
total_lemma = lemma.split("_")
for i in range(len(total_lemma)):
if i == 0:
lemma_nopos = total_lemma[i].split(':')[0][:-2]
else:
lemma_nopos = total_lemma[i].split(':')[0][:-2] + " " + lemma_nopos
return lemma_nopos
def get_lemma(self, s):
s_list = s.split(':')
return s_list[0]
class join_grounds(Action):
"""join two GROUNDS Beliefs in one, with concatenated variables"""
def execute(self, *args):
dateTimeObj = datetime.now()
id_ground = dateTimeObj.microsecond
union = self.get_arg(str(args[1])) + " " + self.get_arg(str(args[2]))
self.assert_belief(GROUND(str(id_ground), self.get_arg(str(args[0])), union))
def get_arg(self, arg):
s = arg.split("'")
return s[3]
class join_cond_grounds(Action):
"""join two COND_GROUNDS Beliefs in one, with concatenated variables"""
def execute(self, *args):
dateTimeObj = datetime.datetime.now()
id_ground = dateTimeObj.microsecond
union = self.get_arg(str(args[1])) + " " + self.get_arg(str(args[2]))
self.assert_belief(COND_GROUND(str(id_ground), self.get_arg(str(args[0])), union))
def get_arg(self, arg):
s = arg.split("'")
return s[3]
class join_routine_grounds(Action):
"""join ROUTINE_GROUNDS Beliefs, with concatenated variables"""
def execute(self, *args):
dateTimeObj = datetime.datetime.now()
id_ground = dateTimeObj.microsecond
union = self.get_arg(str(args[1])) + " " + self.get_arg(str(args[2]))
self.assert_belief(ROUTINE_GROUND(str(id_ground), self.get_arg(str(args[0])), union))
def get_arg(self, arg):
s = arg.split("'")
return s[3]
class append_intent_params(Action):
"""Append intent params considering a prepositions list"""
def execute(self, *args):
parameters_list = self.get_arg(str(args[6]))
location = self.get_arg(str(args[5]))
verb = self.get_arg(str(args[0]))
dav = self.get_arg(str(args[1]))
obj = self.get_arg(str(args[2]))
prep = self.get_arg(str(args[3]))
prep_obj = self.get_arg(str(args[4]))
if prep in ["In"]:
location = prep_obj
else: