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Authoryeye
Submission date2019-05-03 05:34:38.205515
Rating4908
Matches played245
Win rate47.76

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

Source code:

import random
states=['RR', 'RP', 'RS', 'PR', 'PP', 'PS', 'SR', 'SP', 'SS']
class RPSai:
    def __init__(self):
        self.d={}
        self.history=[]
        self.matrix={}
        for i in states:
            self.matrix[i]={'R': {'prob' : 1 / 3,'times' : 0},'P': {'prob' : 1 / 3,'times' : 0},'S': {'prob' : 1 / 3,'times' : 0}}
    def opponentMove(self,oppo_move):
        if oppo_move=="R" or oppo_move=="P" or oppo_move=="S":
            #update markov chain
            if len(self.history)>=2:
                state=self.history[-2]+self.history[-1]
                self.matrix[state][oppo_move]['times'] = self.matrix[state][oppo_move]['times'] + 1
                total = 0
                for i in self.matrix[state]:
                    total += self.matrix[state][i]['times']
                for i in self.matrix[state]:
                    self.matrix[state][i]['prob'] = self.matrix[state][i]['times'] / total
            #update self.history
            self.history.append(oppo_move)
            
            #update dictionary
            if oppo_move in self.d:
                self.d[oppo_move]+=1
            else:
                self.d[oppo_move]=1
    def beatMove(self,expected_oppo_move):
        if expected_oppo_move=="R":
            return "P"
        if expected_oppo_move=="P":
            return "S"
        if expected_oppo_move=="S":
            return "R"
    def predictMovePro(self):
        if len(self.history)<2:
            return random.choice(["R","P","S"])
        if len(self.history)>=2:
            state=self.history[-2]+self.history[-1]
            lst_prob=[]
            lst_time=[]
            for i in self.matrix[state]:
                lst_prob.append(self.matrix[state][i]["prob"])
                lst_time.append(self.matrix[state][i]["times"])
            if max(lst_prob)==min(lst_prob):
                if max(lst_time)==min(lst_time):
                    return random.choice(["R","P","S"])
                else:
                    return self.matrix[state][lst_times.index(max(lst_time))]
            else:
                for i in self.matrix[state]:
                    if self.matrix[state][i]["prob"]==max(lst_prob):
                        return i
    def playMovePro(self):
        return self.beatMove(self.predictMovePro())
me=RPSai()
if input=="":
    output=random.choice(["R","P","S"])
else:
    me.opponentMove(input)
    output=me.playMovePro()