This program has been disqualified.
Author | EbTech |
Submission date | 2011-06-21 01:04:16.129898 |
Rating | 4568 |
Matches played | 2035 |
Win rate | 42.7 |
#descendant or ancestor of a long lineage of Earthling bots (concluding with DNA Werfer 8)?
import random
if not input:
number_of_predictors = 54
predictors = range(number_of_predictors)
predictorscore = range(number_of_predictors)
for i in range(number_of_predictors):
predictors[i] = random.choice(['R','P','S'])
predictorscore[i] = random.random()*0.1;
threat = [0,0,0]
outcome = 0
beat = {'R':'P','P':'S','S':'R'}
nuclease = {'RP':'a','PS':'b','SR':'c','PR':'d','SP':'e','RS':'f','RR':'g','PP':'h','SS':'i'}
limits = [50,17,6]
length = 0
urmoves = ""
mymoves = ""
DNAmoves = ""
output = random.choice(['R','P','S'])
else:
oldoutcome = outcome
if (beat[input] == output):
outcome = 1
elif (input == beat[output]):
outcome = -1
else:
outcome = 0
threat[oldoutcome + 1] *= 0.96
threat[oldoutcome + 1] -= outcome
for i in range(number_of_predictors):
predictorscore[i] *= 0.8
predictorscore[i] += outcome
#History matching
urmoves += input
mymoves += output
DNAmoves += nuclease[input+output]
length += 1
for z in range(3):
limit = min([length-1, limits[z]])
j = limit
while j>=1 and not DNAmoves[length-j:length] in DNAmoves[0:length-1]:
j-=1
if j>=1:
i = DNAmoves.rfind(DNAmoves[length-j:length], 0, length-1)
predictors[0+6*z] = urmoves[j+i]
predictors[1+6*z] = mymoves[j+i]
j = limit
while j>=1 and not urmoves[length-j:length] in urmoves[0:length-1]:
j-=1
if j>=1:
i = urmoves.rfind(urmoves[length-j:length], 0, length-1)
predictors[2+6*z] = urmoves[j+i]
predictors[3+6*z] = mymoves[j+i]
j = limit
while j>=1 and not mymoves[length-j:length] in mymoves[0:length-1]:
j-=1
if j>=1:
i = mymoves.rfind(mymoves[length-j:length], 0, length-1)
predictors[4+6*z] = urmoves[j+i]
predictors[5+6*z] = mymoves[j+i]
for i in range(number_of_predictors/3, number_of_predictors):
predictors[i] = beat[predictors[i - number_of_predictors/3]]
#compare predictors
if random.random() < 0.2*threat[outcome+1]+0.1:
output = random.choice(['R','P','S'])
else:
output = predictors[predictorscore.index(max(predictorscore))]
oldpredictors = predictors