# hybrid

This program has been disqualified.

 Author pyfex Submission date 2011-07-07 14:31:19.453293 Rating 7741 Matches played 1933 Win rate 75.38

## Source code:

``````# See http://overview.cc/RockPaperScissors for more information about rock, paper, scissors
# A hybrid between switching and bayes bot. Randomly choose one of these two strategies
# The idea of this approach is, that it should become more difficult to predict the
# playing style of this bot

if input == '':
import random
import collections
import operator
rps = ['R', 'P', 'S']
beat = {'R': 'P', 'P': 'S', 'S': 'R'}
cede = {'R': 'S', 'P': 'R', 'S': 'P'}
score = {'RR': 0, 'PP': 0, 'SS': 0, 'PR': 1, 'RS': 1, 'SP': 1,'RP': -1, 'SR': -1, 'PS': -1,}
cscore = {'RR': 't', 'PP': 't', 'SS': 't', 'PR': 'b', 'RS': 'b', 'SP': 'b','RP': 'c', 'SR': 'c', 'PS': 'c',}
beatboth = {'RR': 'P', 'PP': 'S', 'SS': 'R', 'PR': 'P', 'RS': 'R', 'SP': 'S','RP': 'P', 'SR': 'R', 'PS': 'S',}
def shift(n, move):
for i in range(n%2):
move = beat[move]
return move

def unshift(n, move):
for i in range(n%2):
move = cede[move]
return move

def counter_prob(probs):
weighted_list = []
for h in ['R', 'P', 'S']:
weighted = 0
for i, p in enumerate(probs):
points = score[h+rps[i]]
weighted += points * p
weighted_list.append((h, weighted))

m = max(weighted_list, key=operator.itemgetter(1))[1]
candidates = [e[0] for e in weighted_list if e[1] == m]
return random.choice(candidates)
hist = ""
patterns = collections.defaultdict(lambda: 10)
output = random.choice(rps)
candidates = []
performance = [0] * 150
results = [0, 0, 0] # losses, ties, wins
opp = my = opp2 = my2 = ""
else:
results[score[output+input]+1] += 1
losses, ties, wins = results

if opp and my:
patterns['ao'+cscore[input+opp]] += 1
patterns['am'+cscore[input+my]] += 1
if opp2 and my2:
patterns['ao2'+cscore[input+opp2]] += 1
patterns['am2'+cscore[input+my2]] += 1

patterns['1o'+opp+input] += 1
patterns['1m'+my+input] += 1
patterns['1b'+my+opp+input] += 1
patterns['2o'+opp2+input] += 1
patterns['2m'+my+input] += 1
patterns['2b'+my+opp+input] += 1

for i in range(min(1+len(hist)/2,6), 0, -1):
patterns[hist[-i*2:]+input] += 1
pattern = patterns.get(hist[-i*2:], "")
if pattern:
for j in range(min(1+len(pattern)/2,6), 0, -1):
idx = pattern[-j*2:].lower()
patterns[idx] = patterns.get(idx, "") + output + input
patterns[hist[-i*2:]] = pattern + output + input

for i, c in enumerate(candidates):
if score[c+input] == 1:
performance[i] += 1
else:
performance[i] = 0

hist += output+input

my = opp = my2 = opp2 = ""
for i in range(min(1+len(hist)/2,6), 0, -1):
pattern = patterns.get(hist[-i*2:], "")
if pattern:
my, opp = pattern[-2:]
for j in range(min(1+len(pattern)/2,6), 0, -1):
pattern2 = patterns.get(pattern[-j*2:].lower(), "")
if pattern2 != "":
my2, opp2 = pattern2[-2:]
break
break
else:
candidates = []

if my and opp:
candidates = [opp, my, beat[opp], cede[opp], beat[my], cede[my]]
for i, a in enumerate(candidates[:]):
for offset in range(3):
candidates.extend([shift(offset+wins, a), shift(offset+wins+ties, a), shift(offset+losses+ties, a), shift(offset+losses, a)])
candidates.extend([unshift(offset+wins, a), unshift(offset+wins+ties, a), unshift(offset+losses+ties, a), unshift(offset+losses, a)])

probs = [1, 1, 1]
if my and opp:
probs = [p * patterns['1o'+opp+h] for p,h in zip(probs, rps)]
probs = [p * patterns['1m'+my+h] for p,h in zip(probs, rps)]
probs = [p * patterns['1b'+my+opp+h] for p,h in zip(probs, rps)]
probs = [p * patterns['ao'+cscore[h+opp]] for p,h in zip(probs, rps)]
probs = [p* patterns['ao'+cscore[h+my]] for p,h in zip(probs, rps)]

if my2 and opp2:
probs = [p * patterns['2o'+opp2+h] for p,h in zip(probs, rps)]
probs = [p * patterns['2m'+my2+h] for p,h in zip(probs, rps)]
probs = [p * patterns['2b'+my2+opp2+h] for p,h in zip(probs, rps)]
probs = [p * patterns['ao2'+cscore[h+my2]] for p,h in zip(probs, rps)]
probs = [p * patterns['am2'+cscore[h+my2]] for p,h in zip(probs, rps)]

s = random.choice(['S', 'B', 'R'])
if s == 'S':
output = random.choice(rps)
if candidates:
m = max(performance)
output = random.choice([candidates[i] for i, p in enumerate(performance) if p == m])
elif s == 'B':
output = counter_prob(probs)
else:
output = beat[random.choice(list(hist))]``````