This program has been disqualified.
Author | Byron Knoll |
Submission date | 2011-06-11 19:44:54.155639 |
Rating | 6779 |
Matches played | 2731 |
Win rate | 69.94 |
import random
# initialization
if input=="":
numPredictors = 10
maxHistoryLength = 50
history1 = ""
history2 = ""
history3 = ""
lastOutput = ""
scores = []
predictions = []
index = 0
while index < numPredictors:
scores.append(0)
predictions.append("")
index+=1
dictionary1 = {}
dictionary2 = {}
dictionary3 = {}
# update scores
index = 0
while index < numPredictors:
if input==predictions[index]:
scores[index]+=1
if (input=="R" and predictions[index]=="P") or (input=="P" and predictions[index]=="S") or (input=="S" and predictions[index]=="R"):
scores[index]-=1
index += 1
# update histories
history1 += input
if len(history1) > maxHistoryLength:
history1 = history1[1:maxHistoryLength+1]
history2 += lastOutput
if len(history2) > maxHistoryLength:
history2 = history2[1:maxHistoryLength+1]
history3 += input + lastOutput
if len(history3) > maxHistoryLength:
history3 = history3[1:maxHistoryLength+1]
# update dictionaries
index = 0
while index < len(history1):
key = history1[index:len(history1)]
if dictionary1.has_key(key):
dictionary1[key] = dictionary1[key] + 1
else:
dictionary1[key] = 1
index+=1
index = 0
while index < len(history2):
key = history2[index:len(history2)-1]
if dictionary2.has_key(key):
dictionary2[key] = dictionary2[key] + 1
else:
dictionary2[key] = 1
index+=1
index = 0
while index < len(history3):
key = history3[index:len(history3)]
if dictionary3.has_key(key):
dictionary3[key] = dictionary3[key] + 1
else:
dictionary3[key] = 1
index+=1
# make prediction (0,1,2 = PPM model opponent)
order = len(history1)-1
while order >= 0:
context = history1[len(history1)-order:len(history1)]
if dictionary1.has_key(context+"R"):
rockCount = dictionary1[context+"R"]
else:
rockCount = 0
if dictionary1.has_key(context+"P"):
paperCount = dictionary1[context+"P"]
else:
paperCount = 0
if dictionary1.has_key(context+"S"):
scissorsCount = dictionary1[context+"S"]
else:
scissorsCount = 0
if rockCount > 0 and rockCount > paperCount and rockCount > scissorsCount:
predictions[0] = "P"
predictions[1] = "S"
predictions[2] = "R"
break
elif paperCount > 0 and paperCount > scissorsCount:
predictions[0] = "S"
predictions[1] = "R"
predictions[2] = "P"
break
elif scissorsCount > 0:
predictions[0] = "R"
predictions[1] = "P"
predictions[2] = "S"
break
order -= 1
# make prediction (3,4,5 = PPM model me)
order = len(history2)-1
while order >= 0:
context = history2[len(history2)-order:len(history2)]
if dictionary2.has_key(context+"R"):
rockCount = dictionary2[context+"R"]
else:
rockCount = 0
if dictionary2.has_key(context+"P"):
paperCount = dictionary2[context+"P"]
else:
paperCount = 0
if dictionary2.has_key(context+"S"):
scissorsCount = dictionary2[context+"S"]
else:
scissorsCount = 0
if rockCount > 0 and rockCount > paperCount and rockCount > scissorsCount:
predictions[3] = "P"
predictions[4] = "S"
predictions[5] = "R"
break
elif paperCount > 0 and paperCount > scissorsCount:
predictions[3] = "S"
predictions[4] = "R"
predictions[5] = "P"
break
elif scissorsCount > 0:
predictions[3] = "R"
predictions[4] = "P"
predictions[5] = "S"
break
order -= 1
# make prediction (6 = random)
predictions[6] = random.choice(["R","P","S"])
# make prediction (7,8,9 = PPM model both)
order = len(history3)-1
while order >= 0:
context = history3[len(history3)-order:len(history3)]
if dictionary3.has_key(context+"R"):
rockCount = dictionary3[context+"R"]
else:
rockCount = 0
if dictionary3.has_key(context+"P"):
paperCount = dictionary3[context+"P"]
else:
paperCount = 0
if dictionary3.has_key(context+"S"):
scissorsCount = dictionary3[context+"S"]
else:
scissorsCount = 0
if rockCount > 0 and rockCount > paperCount and rockCount > scissorsCount:
predictions[7] = "P"
predictions[8] = "S"
predictions[9] = "R"
break
elif paperCount > 0 and paperCount > scissorsCount:
predictions[7] = "S"
predictions[8] = "R"
predictions[9] = "P"
break
elif scissorsCount > 0:
predictions[7] = "R"
predictions[8] = "P"
predictions[9] = "S"
break
order -= 1
# choose move
best = -1000
index = 0
while index < numPredictors:
if scores[index] > best:
best = scores[index]
if predictions[index] == "R":
output = "P"
elif predictions[index] == "P":
output = "S"
else:
output = "R"
index += 1
lastOutput = output