Package ch.idsia.ai.tasks

Examples of ch.idsia.ai.tasks.ProgressTask

21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
        Agent controller = RegisterableAgent.load (args[0]);
        RegisterableAgent.registerAgent (controller);
        EvaluationOptions options = new CmdLineOptions(new String[0]);
        options.setAgent(controller);
        options.setPauseWorld (false);
        Task task = new ProgressTask(options);
        options.setMaxFPS(true);
        options.setVisualization(false);     
        options.setMaxAttempts(1);
        options.setMatlabFileName("");
        task.setOptions(options);
        for (int i = 0; i < repetitions; i++) {
            System.out.println ("Score: " + task.evaluate (controller)[0]);
        }
    }
View Full Code Here
30
31
32
33
34
35
36
37
38
39
40
        Evolvable initial = new SimpleMLPAgent();
        RegisterableAgent.registerAgent ((Agent) initial);
        options.setMaxFPS(true);
        options.setLevelDifficulty(0);
        options.setVisualization(false);
        ProgressTask task = new ProgressTask(options);
        options.setLevelRandSeed((int) (Math.random () * Integer.MAX_VALUE));
        ES es = new ES (task, initial, populationSize);
        System.out.println("Evolving " + initial + " with task " + task);
        final String fileName = "evolved" + (int) (Math.random () * Integer.MAX_VALUE) + ".xml";
        for (int gen = 0; gen < generations; gen++) {
View Full Code Here
32
33
34
35
36
37
38
39
40
41
42
        }
        RegisterableAgent.registerAgent ((Agent) initial);
        options.setMaxFPS(true);
        options.setPauseWorld(false);
        options.setVisualization(false);
        ProgressTask task = new ProgressTask(options);
        int seed = (int) (Math.random () * Integer.MAX_VALUE);
        ES es = new ES (task, initial, populationSize);
        System.out.println("Evolving " + initial + " with task " + task);
        int difficulty = 0;
        final String fileName = "evolved" + (int) (Math.random () * Integer.MAX_VALUE) + ".xml";
View Full Code Here
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
      GlobalOptions.writeFrames = false; //set to true to write frames to disk
      GlobalOptions.TimerOn = false;
      GlobalOptions.dontResetWindowPosition = true;
      EvaluationOptions options = new CmdLineOptions(new String[0]);
      options.setAgent(controller);
      Task task = new ProgressTask(options);
      options.setMaxFPS(false);
      options.setVisualization(true);
      options.setMaxAttempts(1);
      options.setMatlabFileName("");
      options.setLevelLength(length);
      options.setLevelRandSeed(seed);
      options.setLevelDifficulty(difficulty);
      options.setTimeLimit(0);
     
      task.setOptions(options);

      System.out.println("Score: " + ArrayUtils.toString(task.evaluate(controller)));
      System.out.println("Seed: " + options.getLevelRandSeed());
      System.out.println("Difficulty: " + options.getLevelDifficulty());
      seed++;
    }
  }
View Full Code Here
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
            controller = RegisterableAgent.load (args[0]);
            RegisterableAgent.registerAgent (controller);
        }*/
        EvaluationOptions options = new CmdLineOptions(new String[0]);
        //options.setAgent(controller);
        Task task = new ProgressTask(options);
        options.setMaxFPS(false);
        options.setVisualization(false);
        options.setMaxAttempts(1);
        options.setMatlabFileName("");
        options.setLevelRandSeed(seed);
        options.setLevelDifficulty(10);
        GlobalOptions.FPS = GlobalOptions.InfiniteFPS;
        task.setOptions(options);
       
        GA vivarium = new GA(task, new GeneticAgent(), 60);
       
        for (int i = 0; i < 30; i++)
        {
          System.out.println("Best of Gen " + i + ": " + vivarium.getBestFitnesses()[0]);
          vivarium.nextGeneration();
          System.out.flush();
        }

        System.out.println("Score: " + ArrayUtils.toString(task.evaluate(controller)));
        System.out.println("Seed: " + options.getLevelRandSeed());
        System.out.println("Difficulty: " + options.getLevelDifficulty());
        System.out.println("Best Genome: " + vivarium.getBests()[0]);
    }
View Full Code Here
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
    GlobalOptions.currentController = controller.getName();
    GlobalOptions.writeFrames = false; //set to true to write frames to disk
    EvaluationOptions options = new CmdLineOptions(new String[0]);
    options.setAgent(controller);
    Task task = new ProgressTask(options);
    options.setMaxFPS(false);
    options.setVisualization(true);
    options.setMaxAttempts(1);
    options.setMatlabFileName("");
    options.setLevelLength(length);
    options.setLevelRandSeed(seed);
    options.setLevelDifficulty(difficulty);
    task.setOptions(options);

    System.out.println("Score: " + ArrayUtils.toString(task.evaluate(controller)));
    System.out.println("Seed: " + options.getLevelRandSeed());
    System.out.println("Difficulty: " + options.getLevelDifficulty());
  }
View Full Code Here
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
            options.setAgent((Agent)initial);

            options.setMaxFPS(true);
            options.setVisualization(false);

            Task task = new ProgressTask(options);
            ES es = new ES (task, initial, populationSize);

            for (int gen = 0; gen < generations; gen++) {
                es.nextGeneration();
                double bestResult = es.getBestFitnesses()[0];
//                LOGGER.println("Generation " + gen + " best " + bestResult, LOGGER.VERBOSE_MODE.INFO);
                System.out.println("Generation " + gen + " best " + bestResult);
                options.setVisualization(gen % 5 == 0 || bestResult > 4000);
                options.setMaxFPS(true);
                Agent a = (Agent) es.getBests()[0];
                a.setName(((Agent)initial).getName() + df.format(gen));
                RegisterableAgent.registerAgent(a);
                bestAgents.add(a);
                double result = task.evaluate(a)[0];
//                LOGGER.println("trying: " + result, LOGGER.VERBOSE_MODE.INFO);
                options.setVisualization(false);
                options.setMaxFPS(true);
                Easy.save (es.getBests()[0], "evolved.xml");
                if (result > 4000)
View Full Code Here
TOP

Related Classes of ch.idsia.ai.tasks.ProgressTask

  • ch.idsia.scenarios.Evolve
  • ch.idsia.scenarios.GeneticPlay
  • ch.idsia.scenarios.Play
  • ch.idsia.scenarios.PlayForever
  • ch.idsia.scenarios.test.EvolveSingle
  • ch.idsia.scenarios.test.PaperEvolve
  • ch.idsia.scenarios.test.StochasticityTest
  • ch.idsia.tools.Evaluator
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.