# Markov v2

 Author Cabu Submission date 2012-07-31 15:27:15.538879 Rating 7054 Matches played 780 Win rate 68.97

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

## Source code:

``````import random

moves = ['R', 'P', 'S']
beat_move = {'R': 'P', 'P': 'S', 'S': 'R'}

def biaised_rps (R, P, S):
""" Play R, P or S in fonction of their frequencies """
# biaised_rps (1, 1, 1) play 33% R, 33% P and 33% S
# biaised_rps (2, 1, 0) play 66% R, 33% P and  0% S

x = random.random()
if x < R / float (R + P + S):
return 'R'
elif x < (R + P) / float (R + P + S):
return 'P'
else:
return 'S'

output = ''

if input == '':
opp_history = ''

else:
opp_history += input

for length in (100, 90, 80, 70, 60, 50, 40, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1):
# Search for the last longest chain
M = {'R': 0, 'P': 0, 'S': 0}
x = 0
while True:
p = opp_history[x:-1].find (opp_history[-length:])
if p == -1:
break
x += p
M[opp_history[x + length]] += 1
x += 1

# If found: Pick what will be probably the next move and play against it
if x != 0:
next_move = biaised_rps (M['R'], M['P'], M['S'])
output = beat_move[next_move]
break

if output == '':
output = random.choice (moves)``````