def main_handler(ctx):
"""
:param ctx:
Dict
ctx is the context object containing message data, the user who owns the bot instance, and
:return:
The bot's return value will be POSTed to its specified webhook address, if one is provided.
"""
# First create an instance of the API interface
api = MC(ctx)
# Replace 'pass' with your code.
# Try uncommenting the line(s) below to send an email to yourself with the original message.
# api.send_email(ctx['user']['email'], "Original message:\n" + str(ctx['message']),
# subject='Hello from Machine Colony!')
pass
import gym
import matplotlib.pyplot as plt
import numpy as np
from mc import FiniteMCModel as MC
env = gym.make("CliffWalking-v0")
# WARNING: If you try to set eps to a very low value,
# And you attempt to get the m.score() of m.pi, there may not
# be guarranteed convergence.
eps = 10000
S = 4*12
A = 4
START_EPS = 0.7
m = MC(S, A, epsilon=START_EPS)
for i in range(1, eps+1):
ep = []
observation = env.reset()
while True:
# Choosing behavior policy
action = m.choose_action(m.b, observation)
# Run simulation
next_observation, reward, done, _ = env.step(action)
ep.append((observation, action, reward))
observation = next_observation
if done:
break
m.update_Q(ep)
# Decaying epsilon, reach optimal policy
import gym
env = gym.make("Blackjack-v0")
# The typical imports
import gym
import numpy as np
import matplotlib.pyplot as plt
from mc import FiniteMCModel as MC
eps = 1000000
S = [(x, y, z) for x in range(4,22) for y in range(1,11) for z in [True,False]]
A = 2
m = MC(S, A, epsilon=1)
for i in range(1, eps+1):
ep = []
observation = env.reset()
while True:
# Choosing behavior policy
action = m.choose_action(m.b, observation)
# Run simulation
next_observation, reward, done, _ = env.step(action)
ep.append((observation, action, reward))
observation = next_observation
if done:
break
m.update_Q(ep)
# Decaying epsilon, reach optimal policy
m.epsilon = max((eps-i)/eps, 0.1)
import json
import os
import re
OBJECTS_PATH = "./dets/objects/"
RECOG_PATH = "./dets/recogobj/"
FRAME_MDATA_PATH = "./dets/"
if len(sys.argv) < 6:
print "no db arg"
print "legacy.py <db server url> <db server port> <username> <password>"
exit(1)
mc = MC({'serverUrl': sys.argv[1],
'port': int(sys.argv[2]),
'userName': sys.argv[3],
'password': sys.argv[4],
'dbName': sys.argv[5]})
# upload objects (facetraces)
print "uploading objects (facetraces)"
object_files = os.listdir(OBJECTS_PATH)
total_obj_files = len(object_files)
processed_obj_files = 0
for obj_file in object_files:
print "processing file {0}".format(obj_file)
obj_json = open(OBJECTS_PATH + obj_file).read()
obj_data = json.loads(obj_json)
mc.addFaceTrace(obj_data)
processed_obj_files = processed_obj_files + 1
print "uploaded facetrace {0} of {1}".format(processed_obj_files, total_obj_files)
def __init__(self, symbole = 'O', num_tirages_MC = 3, num_descentes_dans_arbre = 7, facteur_uct = 0.0): '''Créer un joueur du symbole indiqué''' MC.__init__(self, symbole, num_tirages_MC) self.num_descentes_dans_arbre = num_descentes_dans_arbre self.facteur_uct = facteur_uct