# db9'''

This program has been disqualified.

 Author momo Submission date 2011-09-01 12:07:22.585834 Rating 7686 Matches played 123 Win rate 78.05

## Source code:

``````import random

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

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

def best(c):
return highest([c[1]-c[2], c[2]-c[0], c[0]-c[1]])

if(1):
if (input == ""):
N = 1
AR1 = 0.85
states = ["R","S","P"]
st = [0,1,2]
sdic = {"R":0, "S":1, "P":2}
table = {}

decay2 = 0.5
res = [[0, 1, -1], [-1, 0, 1], [1, -1, 0]]
total=0
r=0
M = 9
MEM = [2,4,5]
models = [1]*(M*3+1)
state = [0] * (M*3+1)
yo = random.choice(st)
tu = random.choice(st)

pa = (yo, tu)
hi = [pa]
prognosis = [random.choice(st) for i in range(M*3+1)]
choices = []

else:
tu = sdic[input]
pa = (yo,tu)
hi += [pa]

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,[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]
for mem in MEM:
if (N > mem + 1):

p = hi[N-mem-1:N-1]

s = hi[N-mem-2]

key0 = p
for key in [key0, [(i[0],-1) for i in key0], [ (-1,i[1]) for i in key0]]:
k = tuple([s] + key)
if (k in table): table[k] += 1+N*fade

for y in st:
for t in st:
key0 = p
for key in [key0, [(i[0],-1) for i in key0], [(-1,i[1]) for i in key0]]:
k = tuple([(y,t)] + key)
if (k in table):
z = table[k]
count[mem][0][y] += z
count[mem][1][t] += z
countagg = [[],[],[],[],[],[]]
for m in MEM:
countagg[m] = [[count[m][0][i] + count[m][1][(i+0)% 3] for i in st]]
countagg[m] += [[count[m][0][i] + count[m][1][(i+1)% 3] for i in st]]
countagg[m] += [[count[m][0][i] + count[m][1][(i+2)% 3] for i in st]]

i = -3;

for m in MEM:
i += 3; prognosis[i] = best(countagg[m][0])
i += 3; prognosis[i] = best(countagg[m][1])
i += 3; prognosis[i] = best(countagg[m][2])

assert(i+3==3*M)

# 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``````