Examples with SimpleRMHC ga.SimpleRMHC used on opensource projects

Example 16 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class BattleTestEA method main.

public static void main(String[] args) {
    // the number of bandits is equal to the size of the array
    int nTrials = 10;
    int nFitnessEvals = 100;
    EvoAlg ea = new MBanditEA();
    ea = new SimpleRMHC(1);
    int nDims = 10;
    int mValues = 2;
    // SolutionEvaluator evaluator = new EvalMaxM(nDims, mValues);
    SolutionEvaluator evaluator = new EvalBattleGame();
    // ea = new NTupleBanditEA();
    System.out.println("Best fitness stats:");
    System.out.println(runTrials(ea, evaluator, nTrials, nFitnessEvals));
// evaluator.
}

Example 17 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class TestFHT method main.

public static void main(String[] args) {
    int nSamples = 1;
    SimpleRMHC rmhc = new SimpleRMHC(nSamples);
    // now perform the evaluation with and without FHT
    // in order to do this we need access to the solution
    int nDims = 10;
    // make this 2 for bit strings
    int mValues = 2;
    double noise = 1.0;
    NoisySolutionEvaluator evaluator = new EvalMaxM(nDims, mValues, noise);
    // evaluator = new EvalNoisyWinRate(nDims, mValues, noise);
    int nReps = 10000;
    int nFitnessEvals = 500;
    TestFHT testFHT = new TestFHT(evaluator, nFitnessEvals);
    DefaultMutator.defaultPointProb = 1;
    // DefaultMutator.flipAtLeastOneValueDefault = false;
    System.out.println("Problem: " + evaluator.getClass().getSimpleName());
    System.out.println("N Fitness Evals: " + nFitnessEvals);
    System.out.println("Noise: " + noise);
    System.out.println("N Dimensions: " + nDims);
    System.out.println("n Resamples: " + nSamples);
    System.out.println("Algorithm: " + rmhc.getClass().getSimpleName());
    System.out.println("Flip at least one? " + DefaultMutator.flipAtLeastOneValueDefault);
    System.out.println("Mutation probability: " + DefaultMutator.defaultPointProb);
    StatSummary nEvals = new StatSummary("nEvals");
    for (int i = 0; i < nReps; i++) {
        // System.out.println("Trial: " + i);
        foundOpt = false;
        testFHT.runTrial(rmhc);
        nEvals.add(evaluator.nEvals());
        check.add(foundOpt ? 1 : 0);
    // System.out.println(testFHT.nTrueOpt);
    // System.out.println(testFHT.trueFit);
    // System.out.println(testFHT.nFalseOpt);
    // System.out.println();
    }
    System.out.println(nEvals);
    System.out.println("Final results:");
    System.out.println(testFHT.trueFit);
    System.out.println(testFHT.nTrueOpt);
    System.out.println();
    System.out.println(testFHT.nFalseOpt);
    System.out.println();
    System.out.println(check);
}

Example 18 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class GeneralGameRunnerTest method main.

public static void main(String[] args) {
    PlanetWarsLinkState linkState = new PlanetWarsLinkState();
    GeneralGameRunner runner = new GeneralGameRunner().setGame(linkState).setLength(200);
    AbstractMultiPlayer player1, player2;
    GameActionSpaceAdapterMulti.visual = false;
    GameState.includeBuffersInScore = false;
    int idPlayer1 = 0;
    int idPlayer2 = 1;
    ElapsedCpuTimer timer = new ElapsedCpuTimer();
    player1 = new controllers.multiPlayer.discountOLMCTS.Agent(linkState.copy(), timer, idPlayer1);
    // try the evolutionary players
    // GameActionSpaceAdapterMulti.visual = true;
    int nResamples = 1;
    EvoAlg evoAlg = new SimpleRMHC(nResamples);
    int nEvals = 200;
    EvoAlg evoAlg2 = new SlidingMeanEDA().setHistoryLength(20);
    Agent evoAgent1 = new controllers.multiPlayer.ea.Agent(linkState.copy(), timer, evoAlg, idPlayer1, nEvals);
    evoAgent1.sequenceLength = 10;
    // player1 = evoAgent1;
    Agent evoAgent2 = new controllers.multiPlayer.ea.Agent(linkState.copy(), timer, evoAlg, idPlayer2, nEvals);
    evoAgent2.sequenceLength = 10;
    // evoAgent2.setUseShiftBuffer(false);
    player2 = evoAgent2;
    // player2 = new controllers.multiPlayer.ea.Agent(linkState, timer, evoAlg2, idPlayer2, nEvals);
    // player2 = new controllers.multiPlayer.ea.Agent(linkState, timer, new SimpleRMHC(nResamples), idPlayer2, nEvals);
    // player1 = new controllers.multiPlayer.smlrand.Agent();
    // player1 = new controllers.multiPlayer.smlrand.Agent();
    // player2 = new controllers.multiPlayer.doNothing.Agent(linkState.copy(), timer, 1);
    runner.setPlayers(player1, player2);
    int nGames = 100;
    runner.playGames(nGames);
    System.out.println(runner.scores);
}

Example 19 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class EvoAgentSearchSpace method evaluate.

@Override
public double evaluate(int[] x) {
    // create a problem to evaluate this one on ...
    // this should really be set externally, but just doing it this way for now
    GameRunner gameRunner = new GameRunner();
    // search space will need to be set before use
    DefaultMutator mutator = new DefaultMutator(null);
    mutator.pointProb = pointMutationRate[x[pointMutationRateIndex]];
    mutator.flipAtLeastOneValue = flipAtLeastOneBit[x[flipAtLeastOneBitIndex]];
    mutator.totalRandomChaosMutation = false;
    SimpleRMHC simpleRMHC = new SimpleRMHC();
    simpleRMHC.setSamplingRate(nResamples[x[nResamplesIndex]]);
    simpleRMHC.setMutator(mutator);
    EvoAgent evoAgent = new EvoAgent().setEvoAlg(simpleRMHC, getNEvals(x));
    evoAgent.setUseShiftBuffer(useShiftBuffer[x[useShiftBufferIndex]]);
    evoAgent.setSequenceLength(seqLength[x[seqLengthIndex]]);
    EvoAlg evoAlgOpponent = new SimpleRMHC();
    // set up some defaults for opponent
    // previously 400 and 5 respectively
    int nOpponentEvals = 400;
    int opponentSeqLength = 5;
    EvoAgent evoOpponent = new EvoAgent().setEvoAlg(evoAlgOpponent, nOpponentEvals).setSequenceLength(opponentSeqLength);
    // setting to false provides a much weaker opponent
    evoOpponent.setUseShiftBuffer(true);
    // now run a game and return the result
    gameRunner.verbose = false;
    gameRunner.reset();
    gameRunner.setPlayers(evoAgent, evoOpponent);
    gameRunner.playGame();
    double fitness = gameRunner.scores.mean();
    double value = 0;
    if (fitness > 0)
        value = 1;
    if (fitness < 0)
        value = -1;
    logger.log(value, x, false);
    return value;
}

Example 20 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class EvoAgentSearchSpaceAsteroids method evaluate.

@Override
public double evaluate(int[] x) {
    // create a problem to evaluate this one on ...
    // this should really be set externally, but just doing it this way for now
    AsteroidsGameState gameState = new AsteroidsGameState().setParams(params).initForwardModel();
    // search space will need to be set before use
    DefaultMutator mutator = new DefaultMutator(null);
    mutator.pointProb = pointMutationRate[x[pointMutationRateIndex]];
    mutator.flipAtLeastOneValue = flipAtLeastOneBit[x[flipAtLeastOneBitIndex]];
    // setting to true may give best performance
    mutator.totalRandomChaosMutation = false;
    SimpleRMHC simpleRMHC = new SimpleRMHC();
    simpleRMHC.setSamplingRate(nResamples[x[nResamplesIndex]]);
    simpleRMHC.setMutator(mutator);
    EvoAlg sliding = new SlidingMeanEDA();
    EvoAgent evoAgent = new EvoAgent().setEvoAlg(simpleRMHC, getNEvals(x));
    // EvoAgent evoAgent = new EvoAgent().setEvoAlg(sliding, getNEvals(x));
    evoAgent.setUseShiftBuffer(useShiftBuffer[x[useShiftBufferIndex]]);
    evoAgent.setSequenceLength(seqLength[x[seqLengthIndex]]);
    for (int i = 0; i < maxTick; i++) {
        int action = evoAgent.getAction(gameState, 0);
        gameState.next(new int[] { action });
    }
    double fitness = gameState.getScore();
    logger.log(fitness, x, false);
    return fitness;
}