IO2_fightinguuu

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

Source code:

#Iocaine powder based AI

import random

# 2 different lengths of history, 3 kinds of history, both, mine, yours
# 3 different limit length of reverse learning
# 6 kinds of strategy based on Iocaine Powder
num_predictor = 27

if input=="":
    len_rfind = [20]
    limit = [10,20,60]
    beat = { "R":"P" , "P":"S", "S":"R"}
    not_lose = { "R":"PPR" , "P":"SSP" , "S":"RRS" } #50-50 chance
    my_his   =""
    your_his =""
    both_his =""
    list_predictor = [""]*num_predictor
    length = 0
    temp1 = { "PP":"1" , "PR":"2" , "PS":"3",
              "RP":"4" , "RR":"5", "RS":"6",
              "SP":"7" , "SR":"8", "SS":"9"}
    temp2 = { "1":"PP","2":"PR","3":"PS",
                "4":"RP","5":"RR","6":"RS",
                "7":"SP","8":"SR","9":"SS"} 
    who_win = { "PP": 0, "PR":1 , "PS":-1,
                "RP": -1,"RR":0, "RS":1,
                "SP": 1, "SR":-1, "SS":0}
    score_predictor = [0]*num_predictor
    output = random.choice("RPS")
    predictors = [output]*num_predictor
else:
    #update predictors
    #"""
    if len(list_predictor[0])<5:
        front =0
    else:
        front =1
    for i in range (num_predictor):
        if predictors[i]==input:
            result ="1"
        else:
            result ="0"
        list_predictor[i] = list_predictor[i][front:5]+result #only 5 rounds before
    #history matching 1-6
    my_his += output
    your_his += input
    both_his += temp1[input+output]
    length +=1
    for i in range(1):
        len_size = min(length,len_rfind[i])
        j=len_size
        #both_his
        while j>=1 and not both_his[length-j:length] in both_his[0:length-1]:
            j-=1
        if j>=1:
            k = both_his.rfind(both_his[length-j:length],0,length-1)
            predictors[0+6*i] = your_his[j+k]
            predictors[1+6*i] = beat[my_his[j+k]]
        else:
            predictors[0+6*i] = random.choice("RPS")
            predictors[1+6*i] = random.choice("RPS")
        j=len_size
        #your_his
        while j>=1 and not your_his[length-j:length] in your_his[0:length-1]:
            j-=1
        if j>=1:
            k = your_his.rfind(your_his[length-j:length],0,length-1)
            predictors[2+6*i] = your_his[j+k]
            predictors[3+6*i] = beat[my_his[j+k]]
        else:
            predictors[2+6*i] = random.choice("RPS")
            predictors[3+6*i] = random.choice("RPS")
        j=len_size
        #my_his
        while j>=1 and not my_his[length-j:length] in my_his[0:length-1]:
            j-=1
        if j>=1:
            k = my_his.rfind(my_his[length-j:length],0,length-1)
            predictors[4+6*i] = your_his[j+k]
            predictors[5+6*i] = beat[my_his[j+k]]
        else:
            predictors[4+6*i] = random.choice("RPS")
            predictors[5+6*i] = random.choice("RPS")

    for i in range(3):
        temp =""
        search = temp1[(output+input)] #last round
        for start in range(2, min(limit[i],length) ):
            if search == both_his[length-start]:
                temp+=both_his[length-start+1]
        if(temp==""):
            predictors[6+i] = random.choice("RPS")
        else:
            collectR = {"P":0,"R":0,"S":0} #take win/lose from opponent into account
            for sdf in temp:
                next_move = temp2[sdf]
                if(who_win[next_move]==-1):
                    collectR[temp2[sdf][1]]+=3
                elif(who_win[next_move]==0):
                    collectR[temp2[sdf][1]]+=1
                elif(who_win[next_move]==1):
                    collectR[beat[temp2[sdf][0]]]+=1
            max1 = -1
            p1 =""
            for key in collectR:
                if(collectR[key]>max1):
                    max1 = collectR[key]
                    p1 += key
            predictors[6+i] = random.choice(p1)
    
    #rotate 9-27:
    for i in range(9,27):
        predictors[i] = beat[beat[predictors[i-9]]]
        
    #choose a predictor
    len_his = len(list_predictor[0])
    for i in range(num_predictor):
        sum = 0
        for j in range(len_his):
            if list_predictor[i][j]=="1":
                sum+=(j+1)*(j+1)
            else:
                sum-=(j+1)*(j+1)
        score_predictor[i] = sum
    max_score = max(score_predictor)
    #min_score = min(score_predictor)
    #c_temp = {"R":0,"P":0,"S":0}
    #for i in range (num_predictor):
        #if score_predictor[i]==max_score:
        #    c_temp[predictors[i]] +=1
        #if score_predictor[i]==min_score:
        #    c_temp[predictors[i]] -=1
    if max_score>0:
        predict = predictors[score_predictor.index(max_score)]
    else:
        predict = random.choice(your_his)
    output = random.choice(not_lose[predict])