Author | Thomas Holmes |

Submission date | 2011-06-10 17:57:16.531223 |

Rating | 1825 |

Matches played | 5024 |

Win rate | 17.44 |

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

```
#Carbine.py, an [hopefully] intelligent RPS prediction AI.
import random
ROCK = "R"
PAPER = "P"
SCISSOR = "S"
MAX_CYCLE = 10
MIN_CYCLE = 3
output = ""
if input == "":
history = []
weight = {}
count = 0
#change this whole mess to operate only on slices, building lists is
#very unnecessary
for i in range(MAX_CYCLE):
if (len(history) < (MIN_CYCLE - 1)) or (i < (MIN_CYCLE - 1)):
continue
else:
testMoves = history[-(i+1):]
weight = {ROCK:0, PAPER:0, SCISSOR:0}
if len(testMoves) < MAX_CYCLE:
testMoves.insert(i)
else:
break
for j in range(len(history) - i):
testCycle = history[j:j+i]
#if it matches up, add the length of the chain
if testMoves == testCycle:
guess = history[j+i+1]
weight[guess] = weight[guess] + i
r = weight.get(ROCK, 0)
p = weight.get(PAPER, 0)
s = weight.get(SCISSOR, 0)
if (r > p) and (r > s):
output = ROCK
elif p > s:
output = PAPER
else:
output = SCISSOR
if output == "":
output = random.choice([ROCK, PAPER, SCISSOR])
```