Author | blue-tomato |
Submission date | 2015-07-01 01:19:06.362341 |
Rating | 6762 |
Matches played | 506 |
Win rate | 71.54 |
Use rpsrunner.py to play unranked matches on your computer.
#author: blue-tomato
import random
if input == '':
beat = {'R':'P','P':'S','S':'R'}
lose = {'R':'S','P':'R','S':'P'}
class RfindPairs:
def __init__(self):
self.memory = ''
def run(self, input, lastoutput):
self.memory += {('R','R'):'1',('R','P'):'2',('R','S'):'3', \
('P','R'):'4',('P','P'):'5',('P','S'):'6', \
('S','R'):'7',('S','P'):'8',('S','S'):'9'}[(input,lastoutput)]
loc = -1
for i in range(1,min(51,len(self.memory))):
thisloc = self.memory[:-1].rfind(self.memory[-i:])
if thisloc == -1:
break
else:
loc = thisloc+i
if loc == -1:
return 'X'
else:
prediction = self.memory[loc]
return {'1':'P','2':'P','3':'P','4':'S','5':'S','6':'S','7':'R','8':'R','9':'R'}[prediction]
class MetaEnhancedExDecay:
def __init__(self, child, decay):
self.child = child
self.f0 = 0.0
self.f1 = 0.0
self.f2 = 0.0
self.r0prev = 'X'
self.decay = decay
def run(self, input, lastoutput):
if input != '':
if self.r0prev == input:
self.f1 += 2.0
self.f2 -= 2.0
elif self.r0prev == {'R':'P','P':'S','S':'R'}[input]:
self.f0 += 2.1
self.f1 -= 2.0
elif self.r0prev == {'R':'S','P':'R','S':'P'}[input]:
self.f2 += 2.0
self.f0 -= 2.0
self.f0 *= self.decay
self.f1 *= self.decay
self.f2 *= self.decay
r0 = self.child.run(input, lastoutput)
self.r0prev = r0
if r0 == 'X':
return 'X'
if self.f0 > self.f1 and self.f0 >= self.f2:
return r0
if self.f1 >= self.f0 and self.f1 > self.f2:
return {'R':'P','P':'S','S':'R'}[r0]
if self.f2 > self.f0 and self.f2 >= self.f1:
return {'R':'S','P':'R','S':'P'}[r0]
if self.f0 == self.f1 and self.f1 == self.f2:
return 'X'
class Flip:
def __init__(self, child):
self.child = child
def run(self, input, lastoutput):
return {'R':'P','P':'S','S':'R','X':'X'}[self.child.run(lastoutput, input)]
class MetaMerge:
def __init__(self, AIList):
self.AIList = len(AIList)*[0]
self.AIOffset = len(AIList)*[0.0]
self.AIGuess = len(AIList)*['']
self.AIScores = len(AIList)*[0.0]
for i in range(0,len(AIList)):
(offset,AI) = AIList[i]
self.AIList[i] = AI
self.AIOffset[i] = offset
self.AIScores[i] = offset
def run(self, input, lastoutput):
for i in range(0,len(self.AIList)):
if self.AIGuess[i] == beat[input]:
self.AIScores[i] += 1.0
elif self.AIGuess[i] == lose[input]:
self.AIScores[i] -= 1.0
self.AIScores[i] = ((self.AIScores[i]-self.AIOffset[i])*0.97)+self.AIOffset[i]
self.AIGuess[i] = self.AIList[i].run(input, lastoutput)
bestscore = max(self.AIScores)
scoreR = 0
scoreP = 0
scoreS = 0
for i in range(0,len(self.AIList)):
if self.AIScores[i] == bestscore:
if self.AIGuess[i] == 'R':
scoreR += 100
elif self.AIGuess[i] == 'P':
scoreP += 100
elif self.AIGuess[i] == 'S':
scoreS += 100
if scoreR > scoreP and scoreR > scoreS:
return 'R'
if scoreP > scoreS and scoreP > scoreR:
return 'P'
if scoreS > scoreR and scoreS > scoreP:
return 'S'
secondbestscore = -1000000
for i in range(0,len(self.AIList)):
if self.AIScores[i] != bestscore and self.AIScores[i] > secondbestscore:
secondbestscore = self.AIScores[i]
for i in range(0,len(self.AIList)):
if self.AIScores[i] == secondbestscore:
if self.AIGuess[i] == 'R':
scoreR += 1
elif self.AIGuess[i] == 'P':
scoreP += 1
elif self.AIGuess[i] == 'S':
scoreS += 1
if scoreR > scoreP and scoreR >= scoreS:
return 'R'
if scoreP > scoreS and scoreP >= scoreR:
return 'P'
if scoreS > scoreR and scoreS >= scoreP:
return 'S'
return 'X'
AI = MetaMerge([(0.0,MetaEnhancedExDecay(RfindPairs(),0.95)), \
(-0.5,MetaEnhancedExDecay(Flip(RfindPairs()),0.95))])
output = 'X'
else:
output = AI.run(input,lastoutput)
if output == 'X':
output = random.choice('RPS')
lastoutput = output