This program has been disqualified.
Author | zdg |
Submission date | 2011-09-09 23:58:43.797005 |
Rating | 7416 |
Matches played | 147 |
Win rate | 74.15 |
# this combines zai_counts and zai_counts_i series using simple switching
# --------------------- initialization -----------------------------
if not input:
import random
import math
import itertools, operator, functools
# constants
ROUNDS = 1000
R, P, S = 0, 1, 2
RPS_NUM = (R, P, S)
RPS_STR = 'RPS'
WIN, TIE, LOSE = 1, 0, -1
def to_num(h):
return RPS_STR.index(h)
def to_str(i):
return RPS_STR[i]
def play(h1, h2):
return (h1 - h2 + 4) % 3 - 1
def diff(h1, h2):
return (h1 - h2 + 3) % 3
def undiff(h, d):
return (h + d + 3) % 3
def beats(h):
return undiff(h, WIN)
def loses(h):
return undiff(h, LOSE)
def ties(h):
return undiff(h, TIE)
def pick_random(lst):
i = random.randint(0, len(lst) - 1)
return (i, lst[i])
def my_max(val1, val2):
return val1 if val1[1] > val2[1] else val2
def pick_max(lst):
return reduce(my_max, enumerate(lst))
def pick_weighted(lst, sumlst=None):
r = random.uniform(0.0, sumlst or sum(lst))
acc = 0.0
for i, w in enumerate(lst):
acc += w
if r <= acc:
return (i, w)
def skew(lst):
m = max(float(max(lst)), 1.0)
# m = min(lst) / 2.0
for i, x in enumerate(lst):
lst[i] = x / m
# lst[i] = x - m
def random_hand():
return random.choice(RPS_NUM)
COUNT_ORDER_MAX = 7
POWERS3 = tuple(3 ** x for x in xrange(COUNT_ORDER_MAX+1))
# little endian ternary number
def ternary(vec):
return sum(itertools.imap(operator.mul, vec, POWERS3))
def emptycounts(n):
return tuple(tuple([0.0] * 3 for x in RPS_NUM) for i in xrange(n))
def weigh_match(hands_played):
return 10 ** (hands_played / 100.0)
def weigh_order(weight, order):
return weight * 10 ** (order / float(COUNT_ORDER_MAX))
op_counts = tuple(emptycounts(POWERS3[n]) for n in xrange(COUNT_ORDER_MAX+1))
my_counts = tuple(emptycounts(POWERS3[n]) for n in xrange(COUNT_ORDER_MAX+1))
STRATEGIES = 6
DECAY = 0.9
next_hand = [0] * STRATEGIES
strategy_scores = [0.0] * STRATEGIES
my_hands = []
op_hands = []
output = to_str(random_hand())
my_hands.append(to_num(output))
# --------------------- turn -----------------------------
else:
op_hands.append(to_num(input))
hands_played = len(my_hands)
my_last_hand = my_hands[-1]
op_last_hand = op_hands[-1]
my_last_score = play(my_last_hand, op_last_hand)
op_last_score = play(op_last_hand, my_last_hand)
# score the strategies
for i in xrange(STRATEGIES):
last_score = play(next_hand[i], op_last_hand)
strategy_scores[i] *= DECAY
strategy_scores[i] += last_score
# if hands_played % 198 == 0:
# print(strategy_scores)
# update the counts
for order in xrange(min(hands_played - 1, COUNT_ORDER_MAX) + 1):
# update counts for my hands
my_ix = ternary(my_hands[-order-1:-1])
my_counts[order][my_ix][my_last_score][my_last_hand] += weigh_match(hands_played)
# update counts for op hands
op_ix = ternary(op_hands[-order-1:-1])
op_counts[order][op_ix][op_last_score][op_last_hand] += weigh_match(hands_played)
# use counts to determine the next move
next_hand_weights = [[0.0] * 3 for x in xrange(STRATEGIES)]
for order in xrange(min(hands_played, COUNT_ORDER_MAX) + 1):
# use my and op hands to determine the next move
my_ix = ternary(my_hands[-order:] if order != 0 else [])
my_curr_counts = my_counts[order][my_ix]
op_ix = ternary(op_hands[-order:] if order != 0 else [])
op_curr_counts = op_counts[order][op_ix]
for i in RPS_NUM:
next_hand_weights[0][i] += weigh_order(my_curr_counts[WIN][ties(i)], order)
next_hand_weights[1][i] += weigh_order(my_curr_counts[TIE][loses(i)], order)
next_hand_weights[2][i] += weigh_order(my_curr_counts[LOSE][beats(i)], order)
next_hand_weights[3][i] += weigh_order(op_curr_counts[WIN][loses(i)], order)
next_hand_weights[4][i] += weigh_order(op_curr_counts[TIE][loses(i)], order)
next_hand_weights[5][i] += weigh_order(op_curr_counts[LOSE][ties(i)], order)
for i in xrange(STRATEGIES):
skew(next_hand_weights[i])
next_hand[i] = pick_weighted(next_hand_weights[i])[0]
# next_hand[i] = pick_max(next_hand_weights[i])[0]
# if hands_played % 198 == 0:
# print(i, next_hand_weights[i])
best_strategy = pick_max(strategy_scores)
output = to_str(ties(next_hand[best_strategy[0]]))
# output = to_str(ties(next_hand[2]))
my_hands.append(to_num(output))