third-order markov chain

Authorrfw
Submission date2011-05-22 08:05:42.858117
Rating6251
Matches played7403
Win rate59.58

Use rpsrunner.py to play unranked matches on your computer.

Source code:

import random
from collections import defaultdict

ORDER = 3

class RPSEngine(object):
    RPS = {
        "R" : "P",
        "P" : "S",
        "S" : "R",
    }

    def __init__(self):
        self.db = defaultdict(lambda: { "R" : 0, "P" : 0, "S" : 0 })
        self.state = []

    def learn(self, inp):
        if len(self.state) == ORDER:
            self.db[tuple(self.state)][inp] += 1
            del self.state[0]
        self.state.append(inp)

    def decide(self):
        if len(self.state) == ORDER:
            possible = sorted(self.db[tuple(self.state)].iteritems(), key=lambda i: i[1], reverse=True)
            if possible[0][1] == 0:
                return random.choice(self.RPS.keys())
            else:
                return self.RPS[possible[0][0]]
        else:
            return random.choice(self.RPS.keys())

if input == "":
    rpsengine = RPSEngine()
else:
    rpsengine.learn(input)
output = rpsengine.decide()