# detailedbalancet3

 Author momo Submission date 2011-06-11 21:14:02.198119 Rating 6741 Matches played 5336 Win rate 64.88

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

## Source code:

``````import random

def highest(v):
return random.choice([i for i in range(len(v)) if max(v) == v[i]])

if(1):
if (input == ""):
N = 1
mem = 4
AR1 = 0.75
states = ["R","S","P"]
st = [0,1,2]
sdic = {"R":0, "S":1, "P":2}
table = [{},{}]
res = [[0, 1, -1], [-1, 0, 1], [1, -1, 0]]
total=0
r=0
models = [1,1,1, 1,1,1, 1,1,1,1]
M = 3
state = [0] * (M*3+1)
yo= random.choice(st)
tu = random.choice(st)
hi1 = [yo]
hi2 = [tu]
prognosis = [random.choice(st) for i in range(M*3+1)]
choices = []

else:
tu = sdic[input]
hi1.append(yo)
hi2.append(tu)

state = [ AR1 * state[i] + res[prognosis[i]][tu] * models[i] for i in range(M*3+1)]

r = res[yo][tu]
total = total + r

count =  [[0]* 3]* 3

if (N > mem + 1):

p = [hi1[N-mem-1:N-1], hi2[N-mem-1:N-1]]
s = [hi1[N-mem-2], hi2[N-mem-2]]
ins = [0,0]
for i in [0,1]:
ins[i] = tuple([s[1]]+ p[i])
if (ins[i] in table[i]): table[i][ins[i]] += 1+N*fade

for j in st:
if (tuple([j]+ p[i]) in table[i]): count[i][j] = table[i][tuple([j]+p[i])]

prognosis[0] = highest([-c for c in count[0]]) #least freq me
prognosis[3] = highest(count[0]) #highest freq me
prognosis[6] = highest([-c for c in count[1]]) #least freq you
prognosis[9] = highest(count[1]) #highest freq you

# modelrandom
prognosis[3*M] = random.choice(st)

for i in range(M):
prognosis[i*3 + 1] = (prognosis[i*3] + 1) % 3
prognosis[i*3 + 2] = (prognosis[i*3+1] + 1) % 3

best = highest(state)
choices += [best]
yo = prognosis[best]

output = states[yo]

N = N + 1``````