shahradj

import random
from poker import POKER_BOX, Hand, Card
#poker.py can be found at https://gist.github.com/shahradj/1761a6a521c2649bdcc54996d2bb73ec
from gametree import GameTree, ACTIONS
#gametree.py can be found at https://gist.github.com/shahradj/ab6e2ea5ab8cb17ed287dda0c4796ed2
import numpy as np
import pandas as pd
import itertools
import copy
from collections import Counter

shahradj

import numpy as np

ACTIONS = ['r', 'c', 'f']  # RAISE or CALL/CHECK or FOLD


class GameNode:
    def __init__(self, info_set):
        self.info_set = info_set
        self.strategy_sum, self.regret_sum = np.zeros((2, len(ACTIONS)))

shahradj

import itertools
from collections import Counter

# example string representation of card '8 Diamond': '8D'
RANKS = [str(i) for i in range(2, 11)] + ['J', 'Q', 'K', 'A']
SUITS = ['C', 'D', 'H', 'S']
POKER_BOX = [r+s for r,s in itertools.product(RANKS, SUITS)]

class Card:
    def __init__(self, card):

shahradj

import pandas as pd
from scipy.cluster.hierarchy import fclusterdata
from pymongo import MongoClient
import numpy as np
from datetime import *
import json

def saveToRelational(jsonPacket):
	"""
		save the received json packet to a relational database

shahradj

class Game:
    def __init__(self, max_game=100):
        self.p1 = Player('Agent A')
        self.p2 = Player('Agent B')
        self.max_game = max_game
        
    def play(self, avg_regret_matching=False):
        def play_regret_matching():
            for i in xrange(0, self.max_game):
                self.p1.update_strategy()

shahradj

class Prisoners:
    actions = ['SILENCE', 'SNITCH']
    n_actions = 2
    utilities = pd.DataFrame([
        # SILENCE  SNITCH
        [ -2,     -5], # SILENCE
        [ -1,      -3]  # SNITCH
    ], columns=actions, index=actions)