Package ch.idsia.ai.ea

Examples of ch.idsia.ai.ea.ES

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        RegisterableAgent.registerAgent ((Agent) initial);
        options.setMaxFPS(true);
        options.setVisualization(false);
        MultiDifficultyProgressTask task = new MultiDifficultyProgressTask(options);

        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++) {
            task.setStartingSeed((int) (Math.random () * Integer.MAX_VALUE));
            es.nextGeneration();
            double bestResult = es.getBestFitnesses()[0];
            System.out.println("Generation " + gen + " best " + bestResult);
            Evolvable bestEvolvable = es.getBests()[0];
            double[] fitnesses = task.evaluate((Agent) bestEvolvable);
            System.out.printf("%.4f  %.4f  %.4f  %.4f  %.4f\n",
                    fitnesses[0], fitnesses[1], fitnesses[2], fitnesses[3], fitnesses[4]);
            Easy.save (es.getBests()[0], fileName);
        }
        Stats.main(new String[]{fileName, "0"});
    }
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        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++) {
            es.nextGeneration();
            double bestResult = es.getBestFitnesses()[0];
            System.out.println("Generation " + gen + " best " + bestResult);
            Easy.save (es.getBests()[0], fileName);
        }
        Stats.main(new String[]{fileName, "1"});
    }
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        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";
        options.setLevelRandSeed(seed);
        for (int gen = 0; gen < generations; gen++) {
            es.nextGeneration();
            double bestResult = es.getBestFitnesses()[0];
            System.out.println("Generation " + gen + " diff " + difficulty + "  best " + bestResult);
            Easy.save (es.getBests()[0], fileName);
            if (bestResult > 4000) {
                difficulty++;
                options.setLevelDifficulty(difficulty);
                options.setLevelRandSeed(seed);
            }
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            options.setVisualization(false);
            //Task task = new ProgressTask(options);
            MultiSeedProgressTask task = new MultiSeedProgressTask(options);
            task.setNumberOfSeeds(3);
            task.setStartingSeed(0);
            ES es = new ES (task, initial, populationSize);
            System.out.println("Evolving " + initial + " with task " + task);
            for (int gen = 0; gen < generations; gen++) {
                es.nextGeneration();
                double bestResult = es.getBestFitnesses()[0];
                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() + gen);
                RegisterableAgent.registerAgent(a);
                double result = task.evaluate(a)[0];
                options.setVisualization(false);
                options.setMaxFPS(true);
                Easy.save (es.getBests()[0], "evolved.xml");
                if (result > 4000) {
                    initial = es.getBests()[0];
                    break; // Go to next difficulty.
                }
            }
        }
        System.exit(0);
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            options.setVisualization(false);
            //Task task = new ProgressTask(options);
            MultiSeedProgressTask task = new MultiSeedProgressTask(options);
            task.setNumberOfSeeds(3);
            task.setStartingSeed(0);
            ES es = new ES (task, initial, populationSize);
            System.out.println("Evolving " + initial + " with task " + task);
            for (int gen = 0; gen < generations; gen++) {
                //task.setStartingSeed((int)(Math.random () * Integer.MAX_VALUE));
                es.nextGeneration();
                double bestResult = es.getBestFitnesses()[0];
                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() + gen);
                RegisterableAgent.registerAgent(a);
                double result = task.evaluate(a)[0];
                options.setVisualization(false);
                options.setMaxFPS(true);
                Easy.save (es.getBests()[0], "evolved.xml");
                if (result > 4000) {
                    break; //finished
                }
            }
    }
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            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)
                    break; // Go to next difficulty.
            }
        }
        /*// TODO: log dir / log dump dir option
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Related Classes of ch.idsia.ai.ea.ES

  • ch.idsia.ai.Evolvable
  • ch.idsia.scenarios.Evolve
  • ch.idsia.scenarios.EvolveIncrementally
  • ch.idsia.scenarios.EvolveMultiSeed
  • ch.idsia.scenarios.test.EvolveSingle
  • ch.idsia.scenarios.test.EvolveWithChangingSeeds
  • ch.idsia.scenarios.test.PaperEvolve
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