Examples with SimpleRMHC ga.SimpleRMHC used on opensource projects

Example 1 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class SimpleMaxNTest method runOnce.

public static double runOnce() {
    // make an agent to test
    StateObservation noiseFree = new SimpleMaxGame();
    // new NoisyMaxGame();
    StateObservation stateObs = new SimpleMaxGame();
    System.out.println(stateObs.getGameScore());
    System.out.println(stateObs.copy().getGameScore());
    // System.exit(0);
    ElapsedCpuTimer timer = new ElapsedCpuTimer();
    AbstractPlayer player;
    controllers.singlePlayer.sampleOLMCTS.Agent olmcts = new controllers.singlePlayer.sampleOLMCTS.Agent(stateObs, timer);
    controllers.singlePlayer.discountOLMCTS.Agent discountOlmcts = new controllers.singlePlayer.discountOLMCTS.Agent(stateObs, timer);
    controllers.singlePlayer.nestedMC.Agent nestedMC = new controllers.singlePlayer.nestedMC.Agent(stateObs, timer);
    player = olmcts;
    player = discountOlmcts;
    // for the following we can pass the Evolutionary algorithm to use
    int nResamples = 2;
    EvoAlg evoAlg = new SimpleRMHC(nResamples);
    int nEvals = 1000;
    double kExplore = 10;
    int nNeighbours = 100;
    evoAlg = new NTupleBanditEA(kExplore, nNeighbours);
    // DefaultMutator.totalRandomChaosMutation = true;
    Agent.useShiftBuffer = false;
    controllers.singlePlayer.ea.Agent.SEQUENCE_LENGTH = 100;
    player = new controllers.singlePlayer.ea.Agent(stateObs, timer, evoAlg, nEvals);
    nestedMC.maxRolloutLength = 5;
    nestedMC.nestDepth = 5;
    player = nestedMC;
    // in milliseconds
    int thinkingTime = 50;
    int delay = 30;
    // player = new controllers.singlePlayer.sampleRandom.Agent(stateObs, timer);
    // check that we can play the game
    Random random = new Random();
    // this is how many steps we'll take in the actual game ...
    int nSteps = 10;
    ElapsedTimer t = new ElapsedTimer();
    for (int i = 0; i < nSteps && !stateObs.isGameOver(); i++) {
        timer = new ElapsedCpuTimer();
        timer.setMaxTimeMillis(thinkingTime);
        Types.ACTIONS action = player.act(stateObs.copy(), timer);
        // System.out.println("Selected: " + action); //  + "\t " + action.ordinal());
        stateObs.advance(action);
        noiseFree.advance(action);
    // System.out.println(stateObs.getGameScore());
    }
    System.out.println(stateObs.getGameScore());
    System.out.println(noiseFree.getGameScore());
    System.out.println(stateObs.isGameOver());
    System.out.println(t);
    return noiseFree.getGameScore();
}

Example 2 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class SpaceBattleLinkTest method runTrial.

public static double runTrial(boolean runVisible) {
    // make an agent to test
    StateObservation stateObs = new SimpleMaxGame();
    // BattleGameSearchSpace.inject(BattleGameSearchSpace.getRandomPoint());
    // SampleEvolvedParams.solutions[1][2] = 5;
    // BattleGameSearchSpace.inject(SampleEvolvedParams.solutions[1]);
    // BattleGameSearchSpace.inject(SampleEvolvedParams.solutions[2]);
    BattleGameSearchSpace.inject(SampleEvolvedParams.solutions[1]);
    System.out.println("Params are:");
    System.out.println(BattleGameParameters.params);
    // can also overide parameters by setting them directly as follows:
    // BattleGameParameters.loss = 1.1;
    SpaceBattleLinkState linkState = new SpaceBattleLinkState();
    // set some parameters for the experiment
    GameActionSpaceAdapter.useHeuristic = false;
    Agent.useShiftBuffer = true;
    // DefaultMutator.totalRandomChaosMutation = false;
    // // supercl
    // StateObservation stateObs = linkState;
    ElapsedCpuTimer timer = new ElapsedCpuTimer();
    AbstractPlayer player;
    // controllers.singlePlayer.sampleOLMCTS.Agent olmcts =
    // new controllers.singlePlayer.sampleOLMCTS.Agent(linkState, timer);
    player = new controllers.singlePlayer.discountOLMCTS.Agent(linkState, timer);
    // try the evolutionary players
    int nResamples = 2;
    EvoAlg evoAlg = new SimpleRMHC(nResamples);
    double kExplore = 10;
    int nNeighbours = 100;
    int nEvals = 200;
    evoAlg = new NTupleBanditEA(kExplore, nNeighbours);
    // player = new controllers.singlePlayer.ea.Agent(linkState, timer, evoAlg, nEvals);
    controllers.singlePlayer.nestedMC.Agent nestedMC = new controllers.singlePlayer.nestedMC.Agent(linkState, timer);
    nestedMC.maxRolloutLength = 10;
    nestedMC.nestDepth = 2;
    player = nestedMC;
    // in milliseconds
    int thinkingTime = 50;
    int delay = 10;
    // player = new controllers.singlePlayer.sampleRandom.Agent(stateObs, timer);
    // check that we can play the game
    Random random = new Random();
    int nSteps = 500;
    ElapsedTimer t = new ElapsedTimer();
    BattleView view = new BattleView(linkState.state);
    // set view to null to run fast with no visuals
    if (!runVisible)
        view = null;
    if (view != null) {
        new JEasyFrame(view, "Simple Battle Game");
    }
    boolean verbose = false;
    for (int i = 0; i < nSteps && !linkState.isGameOver(); i++) {
        ArrayList<Types.ACTIONS> actions = linkState.getAvailableActions();
        timer = new ElapsedCpuTimer();
        timer.setMaxTimeMillis(thinkingTime);
        Types.ACTIONS action = player.act(linkState.copy(), timer);
        // action = actions.get(random.nextInt(actions.size()));
        if (verbose)
            // + "\t " + action.ordinal());
            System.out.println(i + "\t Selected: " + action);
        linkState.advance(action);
        if (view != null) {
            view.repaint();
            try {
                Thread.sleep(delay);
            } catch (Exception e) {
            }
        }
        if (verbose)
            System.out.println(linkState.getGameScore());
    }
    System.out.println("Game score: " + linkState.getGameScore());
    return linkState.getGameScore();
}

Example 3 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class EvolvePatternTest method main.

public static void main(String[] args) {
    int nTrials = 1;
    SimpleRMHC evoAlg = new SimpleRMHC();
    evoAlg.setMutator(new ConvMutator());
    // evoAlg = new SlidingMeanEDA().setHistoryLength(30);
    // evoAlg = new CompactSlidingGA();
    int nEvals = 50000;
    StatSummary results = new StatSummary();
    EvolvePatternTest ept = new EvolvePatternTest();
    for (int i = 0; i < nTrials; i++) {
        ElapsedTimer timer = new ElapsedTimer();
        results.add(ept.runTrial(evoAlg, nEvals));
        System.out.println(timer);
    }
}

Example 4 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class TestEA method sweepSamplingRate.

public static void sweepSamplingRate(int from, int to) {
    EvoAlg ea = new MBanditEA();
    // SolutionEvaluator evaluator = new EvalMaxM(nDims, mValues, 1.0);
    // SolutionEvaluator noiseFree = new EvalMaxM(nDims, mValues, 0.0);
    SolutionEvaluator evaluator = new EvalNoisyWinRate(nDims, mValues, 1.0);
    SolutionEvaluator noiseFree = new EvalNoisyWinRate(nDims, mValues, 0.0);
    for (int i = from; i <= to; i++) {
        ea = new SimpleRMHC(i);
        // ea = new MBanditEA();
        ea = new NTupleBanditEA();
        StatSummary ss = runTrials(ea, evaluator, noiseFree, nTrials, nFitnessEvals);
        // System.out.format("%d\t %.2f \t %.3f \t %.3f \t %.2f\n", i, ss.mean(), ss.stdErr(), ssOpt.mean(), nOpt.mean());
        System.out.format("%d\t %.3f \t %.3f \t %.3f \t %.2f\t  %.3f\n", i, ss.mean(), nOpt.mean(), ssOpt.mean(), ntOpt.mean(), ntPerf.mean());
    // System.out.format("%d\t %.2f \t %.2f \t %.2f \n", i, ss.mean(), ss.stdErr(), ssOpt.mean());
    }
}

Example 5 with SimpleRMHC

use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.

the class TestEAGraphRunTrials method main.

public static void main(String[] args) throws Exception {
    // create and run a test
    // showing flexibility to create multiple graphs
    int nDims = 100, mValues = 2;
    double noise = 1.0;
    int nEvals = 1000;
    int nTrials = 10;
    NoisySolutionEvaluator solutionEvaluator = new EvalNoisyWinRate(nDims, mValues, noise);
    solutionEvaluator = new EvalMaxM(nDims, mValues, noise);
    // solutionEvaluator = new Eval2DNonLinear(8, noise);
    TestEAGraph tester = new TestEAGraph(solutionEvaluator, nEvals).setColor(Color.red);
    // Set up all the algorithms to test
    SimpleRMHC rmhc1 = new SimpleRMHC(1);
    SimpleRMHC rmhc5 = new SimpleRMHC(5);
    SimpleGA sga = new SimpleGA().setPopulationSize(20).setCrossoverRate(0.5);
    int windowLength = 40;
    CompactSlidingGA slidingGA = new CompactSlidingGA().setHistoryLength(windowLength);
    slidingGA.useBayesUpdates = false;
    // nDims * windowLength / 2;
    slidingGA.K = 1000;
    int nParents = 2;
    CompactBinaryGA cga = new CompactBinaryGA().setParents(nParents);
    // cga.K = nDims / 2; //  * nParents;  // setting from Jialin
    // nDims * nParents;
    cga.K = 1000;
    // cga.nToFlip = 2;
    // add them to the test list
    ArrayList<EvoAlg> evos = new ArrayList<>();
    // evos.add(new SlidingMeanEDA().setHistoryLength(30));
    evos.add(sga);
    evos.add(rmhc1);
    evos.add(rmhc5);
    evos.add(slidingGA);
    evos.add(cga);
    nParents = 20;
    CompactBinaryGA cga2 = new CompactBinaryGA().setParents(nParents);
    cga2.K = nDims * nParents * 2;
    // evos.add(cga2);
    // evos.add(rmhc1);
    // evos.add(rmhc5);
    // evos.add(new SlidingMeanEDA().setHistoryLength(30));
    Color[] colors = { Color.red, Color.green, Color.blue, Color.yellow, Color.cyan, Color.pink, Color.magenta };
    LineChart lineChart = new LineChart().setTitle(String.format("Noisy OneMax, %d dimensions", nDims));
    lineChart.setXLabel("Fitness Evaluations").setYLabel("Noise-Free Fitness");
    lineChart.xAxis = new LineChartAxis(new double[] { 0, 200, 400, 600, 800, 1000 });
    lineChart.yAxis = new LineChartAxis(new double[] { 40, 50, 60, 70, 80, 90, 100 });
    for (int i = 0; i < evos.size(); i++) {
        ElapsedTimer elapsedTimer = new ElapsedTimer();
        tester.setColor(colors[i]);
        TestEvoResults results = tester.runTrials(evos.get(i), nTrials);
        System.out.println("Tested: " + evos.get(i).getClass().getName());
        System.out.println(results.trueOpt);
        System.out.println(elapsedTimer);
        System.out.println();
        lineChart.addLines(results.linePlots);
        lineChart.addLineGroup(results.getLineGroup().setColor(colors[i]).setName(results.name));
    }
    LineGroup pVec = new LineGroup().setName("P-Vec").setColor(Color.white);
    for (ArrayList<Double> extra : extras) {
        // lineChart.addLine(new LinePlot().setColor(Color.white).setData(extra));
        pVec.add(extra);
    }
    // lineChart.addLineGroup(pVec);
    new JEasyFrame(lineChart, "Fitness Evolution");
    String dir = "results/javares/sweda/";
    // String filename = "resultsOneMax.png";
    String filename = "resultsOneMaxPVec.png";
    lineChart.saveImage(dir, filename);
}