# Granatewerfer 2

This program has been disqualified.

 Author dllu Submission date 2011-05-25 16:32:24.095211 Rating 5000 Matches played 2 Win rate 50.0

## Source code:

import random

lastmatch =0
lastmatch1=0
lastmatch2=0

limit = 12

predictors=range(14)
best=-100

for i in range(14):
predictors[i]=random.choice(['R','P','S'])

if not input:
oldpredictors=range(14)
urmoves=""
mymoves=""
output=random.choice(['R','P','S'])
predictorscore=[1.2,0.7,0.7,0.6,0.6,0.6,0,0,0,0,0,0,0,0]

rockRating = scissorsRating = paperRating = 0
rockRating2 = scissorsRating2 = paperRating2 = 0
else:
for i in range(14):
predictorscore[i]*=0.87
if input==oldpredictors[i]:
predictorscore[i]+=0.11
elif input=={'R':'S', 'P':'R', 'S':'P'}[oldpredictors[i]]:
predictorscore[i]-=0.10
else:
predictorscore[i]-=0.03

#Predictor 0-11: History matching
urmoves+=input
done=0
done1=0
done2=0

for i in range(len(urmoves)-1,limit+1,-1):
match1=0
match2=0
fail=[0,0,0]
j=1
while j<=i:
if mymoves[i-j]==mymoves[len(urmoves)-j] and not done1:
match1+=1
if match1>lastmatch1:
lastmatch1=match1
predictors[2]=urmoves[i]
predictors[3]=mymoves[i]
if match1>limit:
done1=1
elif not done1:
match1=0
fail[1]=1
if urmoves[i-j]==urmoves[len(urmoves)-j] and not done2:
match2+=1
if match2>lastmatch2:
lastmatch2=match2
predictors[4]=urmoves[i]
predictors[5]=mymoves[i]
if match2>limit:
done2=1
elif not done2:
match2=0
fail[2]=1
if done1 and done2 or fail[2]==1 and fail[1]==1:
break
j+=1

if done and done1 and done2 or i<len(urmoves)-200:
break

predictors[1]={'R':'P','P':'S','S':'R'}[predictors[1]]
predictors[3]={'R':'P','P':'S','S':'R'}[predictors[3]]
predictors[5]={'R':'P','P':'S','S':'R'}[predictors[5]]

#Predictor 7-12: Opponent plays like Predictor 1-6
for i in range(7,12):
predictors[i] = {'R':'S','P':'R','S':'P'}[predictors[i-6]]

#Predictor 13: Opponent plays like Boltzmann counter
rockRating *= 0.95
scissorsRating *= 0.95
paperRating *= 0.95
if mymoves[len(mymoves)-1] == "R":
paperRating += 0.1
scissorsRating -= 0.1
elif mymoves[len(mymoves)-1] == "P":
scissorsRating += 0.1
rockRating -= 0.1
elif mymoves[len(mymoves)-1] == "S":
rockRating += 0.1
paperRating -= 0.1
if rockRating>scissorsRating and rockRating>paperRating:
predictors[12] = "R"
elif paperRating>scissorsRating:
predictors[12] = "P"
else:
predictors[12] = "S"

#Predictor 14: I play like Boltzmann counter
rockRating2 *= 0.95
scissorsRating2 *= 0.95
paperRating2 *= 0.95
if input=='R':
rockRating2+=0.1
paperRating2-=0.1
elif input=='P':
paperRating2+=0.1
scissorsRating2-=0.1
else:
scissorsRating2+=0.1
rockRating2=0.1
if rockRating2>scissorsRating2 and rockRating2>paperRating2:
predictors[13] = "R"
elif paperRating2>scissorsRating2:
predictors[13] = "P"
else:
predictors[13] = "S"

#compare predictors
for i in [2,4,3,5,13,8,9,10,11,12]:
if predictorscore[i]>best:
output = predictors[i]
best = predictorscore[i]

output = {'R':'P','P':'S','S':'R'}[output] #attempt to win
if len(mymoves)%17==11 or best<0:
output = random.choice(['R','P','S'])
mymoves+=output

for i in range(14):
oldpredictors[i]=predictors[i]