Author | zdg |

Submission date | 2011-09-08 04:10:51.892723 |

Rating | 6713 |

Matches played | 2700 |

Win rate | 64.22 |

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

```
# tries to use higher differences to predict op's next move
import random
def to_num(h):
return 'RPS'.index(h)
def to_str(i):
return 'RPS'[i]
def play(h1, h2):
return (h1 - h2 + 4) % 3 - 1
def beats(h):
return (h + 1) % 3
def loses(h):
return (h + 2) % 3
def ties(h):
return h
def diff(h1, h2):
return (h1 - h2 + 3) % 3
def rotate(h, r):
return (h + r + 3) % 3
def randix(pvec=None):
if pvec is None:
return random.randint(0,2)
r = random.uniform(0.0, sum(pvec))
acc = 0.0
for (i,p) in enumerate(pvec):
acc += p
if r <= acc:
return i
return random.randint(0,2)
def last_repeats(lst, cutoff):
repeats = 1
last = lst[-1]
for i in xrange(len(lst) - 2, -1, -1):
if lst[i] == last and repeats < cutoff:
repeats += 1
else:
break
return repeats
# start
if input == '':
ROUNDS = 1000
R = 0
P = 1
S = 2
RPS = [R,P,S]
WIN = 1
TIE = 0
LOSE = -1
# this is a magic number
# some numbers work well against rfind2 and bayes14
# however some other numbers, even right next to the ones that work, fail miserably
# eg. 39 will win against bayes14 i.e. win 30/30 matches
# however 38 against bayes14 results in only 3/30 wins
ORDER_MAX = 35
diffs = tuple([] for n in xrange(ORDER_MAX+1))
# diff_counts = tuple([0.0] * 3 for n in xrange(ORDER_MAX+1))
my_hands = []
op_hands = []
output = to_str(randix())
my_hands.append(to_num(output))
else:
op_hands.append(to_num(input))
hands = len(my_hands)
# update the diffs and counts
diffs[0].append(op_hands[-1])
# curr_diff_count = diff_counts[0]
curr_diffs = diffs[0]
curr_last_diff = curr_diffs[-1]
repeats = last_repeats(curr_diffs, 10)
# curr_diff_count[curr_last_diff] = last_repeats(curr_diffs, 10)
# curr_diff_count[beats(curr_last_diff)] = 0
# curr_diff_count[loses(curr_last_diff)] = 0
best_choice = (repeats, 0, curr_last_diff)
for i in xrange(1, min(hands, ORDER_MAX + 1)):
diffs[i].append(diff(diffs[i-1][-1], diffs[i-1][-2]))
# curr_diff_count = diff_counts[i]
curr_diffs = diffs[i]
curr_last_diff = curr_diffs[-1]
repeats = last_repeats(curr_diffs, 10)
# curr_diff_count[curr_last_diff] = last_repeats(curr_diffs, 10)
# curr_diff_count[beats(curr_last_diff)] = 0
# curr_diff_count[loses(curr_last_diff)] = 0
best_choice = max(best_choice, (repeats, i, curr_last_diff))
# if hands % 198 == 0:
# print(i, diffs[i][-1], diff_counts[i])
best_level = best_choice[1]
move = best_choice[2]
for i in xrange(best_level - 1, -1, -1):
move = rotate(diffs[i][-1], move)
# if hands % 198 == 0:
# print('best', best_level, best_choice)
# print('move', move)
prediction = move
output = to_str(beats(prediction))
my_hands.append(to_num(output))
```