iocane-antidote_v6

This program has been disqualified.

Source code:

from random import *

#Inspired by dllu and his evil werfer-bots, now looking for various version of history ("us", "me", "yu")
#the code is a mess, but meh..

#removed 'random' strategy

if input == "":
    c_to_n = {'R':0, 'P':1, 'S':2}
    cc_to_m = {'rR':0, 'rP':1, 'rS':2,
               'pR':3, 'pP':4, 'pS':5,
               'sR':6, 'sP':7, 'sS':8}
    win_set  = ['rP', 'pS', 'sR']
    draw_set = ['rR', 'pP', 'sS']
    lose_set = ['rS', 'pR', 'sP']
    shift1 = {'R':'P', 'P':'S', 'S':'R'}
    shift2 = {'R':'S', 'P':'R', 'S':'P'}
    shift3 = {'R':'R', 'P':'P', 'S':'S'}
    random_moves = 10
    decay = 0.6
    weight_0th_order_us = 1
    weight_1st_order_us = 1
    weight_2nd_order_us = 1
    weight_0th_order_me = 1
    weight_1st_order_me = 1
    weight_2nd_order_me = 1
    weight_0th_order_yu = 1
    weight_1st_order_yu = 1
    weight_2nd_order_yu = 1
    prediction_0th_order_us = choice(['R','P','S'])
    prediction_1st_order_us = choice(['R','P','S'])
    prediction_2nd_order_us = choice(['R','P','S'])
    prediction_0th_order_me = choice(['R','P','S'])
    prediction_1st_order_me = choice(['R','P','S'])
    prediction_2nd_order_me = choice(['R','P','S'])
    prediction_0th_order_yu = choice(['R','P','S'])
    prediction_1st_order_yu = choice(['R','P','S'])
    prediction_2nd_order_yu = choice(['R','P','S'])
    history_us = ''
    history_me = ''
    history_yu = ''
    max_match_length = 20
    output = choice(['R','P','S'])
else:
    history_us += input.lower() + output
    history_me += output
    history_yu += input
    if len(history_me) > random_moves:
        weight_0th_order_us *= decay
        weight_1st_order_us *= decay
        weight_2nd_order_us *= decay
        weight_0th_order_me *= decay
        weight_1st_order_me *= decay
        weight_2nd_order_me *= decay
        weight_0th_order_yu *= decay
        weight_1st_order_yu *= decay
        weight_2nd_order_yu *= decay
        if prediction_0th_order_us == input:
            weight_0th_order_us += 1
        elif prediction_1st_order_us == input:
            weight_1st_order_us += 1
        else:
            weight_2nd_order_us += 1
        if prediction_0th_order_me == input:
            weight_0th_order_me += 1
        elif prediction_1st_order_me == input:
            weight_1st_order_me += 1
        else:
            weight_2nd_order_me += 1
        if prediction_0th_order_yu == input:
            weight_0th_order_yu += 1
        elif prediction_1st_order_yu == input:
            weight_1st_order_yu += 1
        else:
            weight_2nd_order_yu += 1
        #####################################################################
        suffix = ''
        for d in range(max_match_length, 0, -1):
            prefix = history_us[-d*2:]
            i = history_us[:-2].rfind(prefix)
            if i > -1:
                suffix = history_us[i + d*2]
                break
        #make nth order predictions
        if suffix != '':
            assert suffix in ['r','p','s']
            prediction_0th_order_us = suffix.upper()
            prediction_1st_order_us = shift2[suffix.upper()]
            prediction_2nd_order_us = shift1[suffix.upper()]
        else:
            prediction_0th_order_us = choice(['R','P','S'])
            prediction_1st_order_us = choice(['R','P','S'])
            prediction_2nd_order_us = choice(['R','P','S'])
        #####################################################################
        suffix = ''
        for d in range(max_match_length, 0, -1):
            prefix = history_me[-d:]
            i = history_me[:-1].rfind(prefix)
            if i > -1:
                suffix = history_me[i + d]
                break
        #make nth order predictions
        if suffix != '':
            assert suffix in ['R','P','S']
            prediction_0th_order_me = shift1[suffix]
            prediction_1st_order_me = shift3[suffix]
            prediction_2nd_order_me = shift2[suffix]
        else:
            prediction_0th_order_me = choice(['R','P','S'])
            prediction_1st_order_me = choice(['R','P','S'])
            prediction_2nd_order_me = choice(['R','P','S'])
        #####################################################################
        suffix = ''
        for d in range(max_match_length, 0, -1):
            prefix = history_yu[-d:]
            i = history_yu[:-1].rfind(prefix)
            if i > -1:
                suffix = history_yu[i + d]
                break
        #make nth order predictions
        if suffix != '':
            assert suffix in ['R','P','S']
            prediction_0th_order_yu = suffix
            prediction_1st_order_yu = shift2[suffix]
            prediction_2nd_order_yu = shift1[suffix]
        else:
            prediction_0th_order_yu = choice(['R','P','S'])
            prediction_1st_order_yu = choice(['R','P','S'])
            prediction_2nd_order_yu = choice(['R','P','S'])
        #####################################################################
        weights = [weight_0th_order_us, weight_1st_order_us, weight_2nd_order_us,
                   weight_0th_order_me, weight_1st_order_me, weight_2nd_order_me,
                   weight_0th_order_yu, weight_1st_order_yu, weight_2nd_order_yu]
        responses = [shift1[prediction_0th_order_us], shift1[prediction_1st_order_us], shift1[prediction_2nd_order_us],
                     shift1[prediction_0th_order_me], shift1[prediction_1st_order_me], shift1[prediction_2nd_order_me],
                     shift1[prediction_0th_order_yu], shift1[prediction_1st_order_yu], shift1[prediction_2nd_order_yu]]
        #####################################################################
        for i in range(len(weights)):
            if random() < weights[i] / sum(weights[i:]):
                output = responses[i]
                break
    else:
        output = choice(['R','P','S'])