StratCounter v5 + RNGFloat

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

Source code:

import random
def beats(move, oppMove): #Score of a game, 1 = win 0.5 = tie 0 = loss
        s = move + oppMove
        if s == "RS" or s == "PR" or s == "SP":
                return 1
        if move == oppMove:
                return 0.5
        return 0
def toInt(move): #Turns RPS into 012
        if move == "R":
                return 0
        if move == "P":
                return 1
        return 2
def greatest(freq):
        if freq[0] > freq[1] and freq[0] > freq[2]:
                return 0
        if freq[1] > freq[2]:
                return 1
        return 2
def weights(freq):
        w = [0,0,0]
        for i in range(3):
                if freq[i] > (1.0 / 3):
                        w[i] = (freq[i] - (1.0 / 3))**5
                else:
                        w[i] = -((1.0 / 3) - freq[i])**5
        return w
if (input == ""): #Initialize
        match = 0
        wonGamesWeighted = 0
        totalGamesWeighted = 0
        weightCoeff = 0.9
        move = "R"
        lastInput = "R"
        lastMove = "R"
        realMove = "R"
        gameRandom = True
        #Game history info
        loopHistory = []
        loopHistoryWeighted = []
        loopSize = 5
        for i in range(loopSize):
                loopHistory.append([])
                loopHistoryWeighted.append([])
                for j in range(i+1):
                        loopHistory[i].append([0,0,0])
                        loopHistoryWeighted[i].append([0,0,0])
        moveHistory = []
        moveHistoryWeighted = []
        for i in range(3):
                moveHistory.append([])
                moveHistoryWeighted.append([])
                for j in range(3):
                        moveHistory[i].append([0,0,0])
                        moveHistoryWeighted[i].append([0,0,0])
        moveModes = [0,0,0]
        moveModesMe = [0,0,0]
        moveModesWeighted = [0,0,0]
        moveModesMeWeighted = [0,0,0]
        commonMoves = []
        commonMovesWeighted = []
        for i in range(3):
                commonMoves.append([])
                commonMovesWeighted.append([])
                for j in range(3):
                        commonMoves[i].append([0,0,0])
                        commonMovesWeighted[i].append([0,0,0])
else: #After the first game
        #Calculate accuracy
        match += 1
        wonGamesWeighted *= weightCoeff
        totalGamesWeighted *= weightCoeff
        wonGamesWeighted += beats(move, input)
        totalGamesWeighted += 1
        accuracy = wonGamesWeighted / totalGamesWeighted
        gameRandom = random.uniform(0,1) > accuracy
        #Loop checker
        for i in range(loopSize):
                for j in range(i):
                        for m in range(3):
                                loopHistoryWeighted[i][j][m] *= weightCoeff
        for i in range(loopSize):
                loopHistory[i][match % (i+1)][toInt(input)] += 1
                loopHistoryWeighted[i][match % (i+1)][toInt(input)] += 1
        #Last turn checker
        for i in range(3):
                for j in range(3):
                        for m in range(3):
                                moveHistoryWeighted[i][j][m] *= weightCoeff
        moveHistory[toInt(lastInput)][toInt(lastMove)][toInt(input)] += 1
        moveHistoryWeighted[toInt(lastInput)][toInt(lastMove)][toInt(input)] += 1
        for m in range(3):
                moveModesWeighted[m] *= weightCoeff
                moveModesMeWeighted[m] *= weightCoeff
        #Common move checker
        for i in range(3):
                for j in range(3):
                        for m in range(3):
                                commonMovesWeighted[i][j][m] *= weightCoeff
                moveModesWeighted[i] *= weightCoeff
                moveModesMeWeighted[i] *= weightCoeff
        commonMoves[greatest(moveModes)][greatest(moveModesMe)][toInt(input)] += 1
        commonMovesWeighted[greatest(moveModesWeighted)][greatest(moveModesMeWeighted)][toInt(input)] += 1
        moveModes[toInt(input)] += 1
        moveModesWeighted[toInt(input)] += 1
        moveModesMe[toInt(realMove)] += 1
        moveModesMeWeighted[toInt(realMove)] += 1
        #Combines different possibile strategies
        strategies = []
        for i in range(loopSize):
                strategies.append(loopHistory[i][match % (i+1)])
                strategies.append(loopHistoryWeighted[i][match % (i+1)])
        strategies.append(moveHistory[toInt(input)][toInt(realMove)])
        strategies.append(moveHistoryWeighted[toInt(input)][toInt(realMove)])
        strategies.append(commonMoves[greatest(moveModes)][greatest(moveModesMe)])
        strategies.append(commonMovesWeighted[greatest(moveModesWeighted)][greatest(moveModesMeWeighted)])
        probability = [0,0,0]
        for s in strategies:
                w = weights(s)
                for i in range(3):
                        probability[i] += w[i]
        lastMove = realMove
        g = greatest(probability)
        if g == 0:
                move = "P"
        elif g == 1:
                move = "S"
        else:
                move = "R"
output = move
if gameRandom: #Overwrite with random move to confuse opponent
        output = random.choice(["R","P","S"])
lastInput = input
realMove = output