def choose_goals(data,
agents,
quests_per_agent=3,
attempts_per_agent=12,
verbose=True):
""" Chooses goals based on preferences, by creating goals stochastically and
rating them according to action costs """
#data = "world/bge/"
domain = "domain.pddl"
for _ in range(attempts_per_agent):
if attempts_per_agent < 2:
goals[:] = []
random_goals(agents)
if attempts_per_agent < 2:
return
good_goals = []
scores = []
for agent in agents:
all_plans = []
while len(all_plans) < attempts_per_agent:
#print(goals[0])
#agent = agents[0]
create(data, [agent])
if verbose:
print("Wait")
#time.sleep(2)
calculating = [questPlanning.plan_quest(agent)]
too_long = 180 # 3 minutes
thinking_time = time.perf_counter()
thinking_timelast = thinking_time
while not finished_thinking(calculating):
time.sleep(0.5)
thinking_timelast += 0.5
if thinking_time + too_long < thinking_timelast:
calculating[0].kill()
print("Took too long!")
break
translation, quest, NPCNames = questTranslation.interpret(data)
if quest == []:
quest = ['Cluster']
score = rate_plan(quest)
if verbose:
print(quest)
print(score)
all_plans.append((score, goals[0], quest))
goals.pop(0)
# Maybe make it choose the longest quest in case of equal scores?
if len(all_plans) == attempts_per_agent:
all_plans = sorted(all_plans)
good_goals.append(all_plans[0][1])
scores.append(all_plans[0][0])
if verbose:
print(good_goals[-1], all_plans[0][0])
if verbose:
print("Should be empty now:")
print(goals)
goals.extend(good_goals)
if verbose:
print("---------------------------------")
print("Quests chosen by the agents :")
print(goals)
print(scores)
def main():
data = "world"
domain = "domain.pddl"
#agents = sorted(["baker", "king", "lumberjack", "blacksmith", "merchant", "guard", "daughter"])
agents = sorted(["Jafar", "Aladdin", "Jasmine", "Genie", "Dragon"])
motivation_count = dict()
motivations = [
"Knowledge", "Comfort", "Reputation", "Serenity", "Protection",
"Conquest", "Wealth", "Ability", "Equipment"
]
for motiv in motivations:
motivation_count[motiv] = 0
motivation_count["Not found"] = 0
print(motivation_count)
emptyOrComplete = 0
quest_log = open("quest_log.txt", "w")
too_long = 600 # 10 minutes
run = 1000
while run > 0:
write_domains(data, domain, agents,
worldManagementAladdin2.preferences)
worldManagementAladdin2.create(data,
agents,
attempts_per_agent=4,
genesis=True,
verbose=False)
calculating = []
opened_files = []
for agent in agents:
calculating.append(questPlanning.plan_quest(agent))
#opened_files.append(open(os.path.join(data,agent+".soln"),"w"))
#calculating.append(subprocess.Popen([os.path.join("metricff","Metric-FF-v2.1","ff"), '-o', os.path.join(data,"domain"+agent+".pddl"), '-f', os.path.join(data,agent+".pddl"), '-s', '3'],stdout=opened_files[-1]))
thinking_time = time.clock()
thinking_timelast = thinking_time
print('Thinking')
while not finished_thinking(calculating):
time.sleep(0.5)
print(".", end=".")
sys.stdout.flush()
thinking_timelast += 0.5
#print(thinking_timelast)
if thinking_time + too_long < thinking_timelast:
print(thinking_time)
print("Took too long!")
for stillcalculating in calculating:
if stillcalculating.poll() == None:
stillcalculating.kill()
break
for opened_file in opened_files:
opened_file.close()
print("Done")
translations, formalplans = questTranslation.interpret(data)
#print(formalplans)
motivations = [
questClassification.classify_fuzzy(formalplan)
for formalplan in formalplans
]
for formalplan, motivation in zip(formalplans, motivations):
#print(translation,motivation)
if len(formalplan) < 1:
emptyOrComplete += 1
else:
print(" ".join(formalplan) + " " + motivation[0])
quest_log.write(" ".join(formalplan))
quest_log.write(" m:" + motivation[0])
quest_log.write("\n\n")
motivation_count[motivation[0]] += 1
"""
for formalplan in formalplans:
#print(formalplan)
if len(formalplan) < 1:
emptyOrComplete += 1
else:
print(" ".join(formalplan))
quest_log.write(" ".join(formalplan))
quest_log.write("\n\n")
"""
print(motivation_count)
print(emptyOrComplete)
run -= 1
quest_log.close()