Author | zdg |

Submission date | 2011-09-04 02:12:29.701729 |

Rating | 6485 |

Matches played | 2660 |

Win rate | 64.85 |

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

```
# searching for a past pattern and using it to predict the opponent's next move
# seems like only matching opponent's hands is better than trying to match opponents and own hands
# also only consider patterns after which the opponent wins or ties, since the opponent is more likely to play those hands
import math
import random
# the hand that beats this hand
beats = {'R':'P', 'P':'S', 'S':'R'}
def randHand():
return random.choice(['R', 'P', 'S'])
def win(mine, other):
return mine == beats[other]
def randWeightedHand(ps):
r = random.random()
if r < ps['R']:
return 'R'
elif r < ps['R'] + ps['P']:
return 'P'
else:
return 'S'
# finds the length of the match from searchIndex and matchIndex leftward
def searchPatternLengthBackwards(lst, searchIndex, matchIndex, indexLimit, lengthLimit):
length = 0
while searchIndex >= indexLimit and matchIndex >= indexLimit and \
length < lengthLimit and lst[searchIndex] == lst[matchIndex]:
searchIndex -= 1
matchIndex -= 1
length += 1
return length
# calculates the weight of a pattern match based on length and distance
# the distance is from the index where the match is found to the current playing index
def weighPattern(length, lengthLimit, distance, distanceLimit):
if length > 0:
temp = length * length
temp2 = temp * temp
lengthWeight = temp2
distanceWeight = ((distanceLimit - distance) / float(distanceLimit)) + 1
return lengthWeight * distanceWeight
else:
return 0
# calculates the weights of the opponent's next move
def calculateWeights(lst, index, distanceLimit, lengthLimit):
indexLimit = index - distanceLimit
weights = {'R':0.0, 'P':0.0, 'S':0.0}
for i in xrange(index - 1, indexLimit - 1, -1):
length = searchPatternLengthBackwards(lst, i, index, indexLimit, lengthLimit)
distance = index - i
# count it only if after that pattern was a tie or a loss
if not win(my_hands[i+1], lst[i+1]):
weight = weighPattern(length, lengthLimit, distance, distanceLimit)
if weight > 0:
weights[lst[i+1]] += weight
return weights
# uses the calculated weights to make a prediction about the opponent's next hand
def predict(lst, index, distanceLimit, lengthLimit, cutoffWeight):
weights = calculateWeights(lst, index, distanceLimit, lengthLimit)
sum = weights['R'] + weights['P'] + weights['S']
if sum < cutoffWeight:
return randHand()
else:
weights['R'] /= sum
weights['P'] /= sum
weights['S'] /= sum
return randWeightedHand(weights)
# start of main code
if input == '':
hands_played = []
my_hands = []
hands = 1
output = randHand()
lastHand = output
else:
hands_played.append(input)
my_hands.append(lastHand)
distanceLimit = min(hands - 1, 100)
lengthLimit = min(hands - 1, 30)
prediction = predict(hands_played, hands - 1, lengthLimit, distanceLimit, 0.5)
output = beats[prediction]
lastHand = output
hands += 1
```