Package eas.users.students.dominikColling.rocket.brain

Examples of eas.users.students.dominikColling.rocket.brain.DomPhysNeuroBrain


  public List<SingleParameter> getParameters() {
      List<SingleParameter> list = super.getParameters();
      ParCollection params = GlobalVariables.getPrematureParameters();
     
      list.addAll(new DomPhysAgent(0, null, "", 0.0f, params, 0).getParameters());
      list.addAll(new DomPhysNeuroBrain(null, 0, null, params).getParameters());
     
     
      return list;
  }
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      for (int l = 0; l < popSize; l++) {
        DomPhysAgent agent = agenten.getAgent(l);
       
        //if(saveLoad == 0 || saveLoad == 1) {
          DomPhysNeuroBrain hirn = new DomPhysNeuroBrain(agent, i, env.getRand(), params);
          agent.implantBrain(hirn);
          i++;
        //}
     
      Vector2D startPosition = startPositionen.get(l);
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          System.out.println("GROESSE: " + netPop.getSize());

          for (int l = 1; l < popSize; l++) {
            DomPhysAgent agent = agenten.getAgent(l);

            DomPhysNeuroBrain hirn = new DomPhysNeuroBrain(agent, netPop.getNet(l).getId(), env.getRand(), netPop.getNet(l));
            agent.implantBrain(hirn);

          }
          DomPhysAgent agent = agenten.getAgent(0);

          DomPhysNeuroBrain hirn = new DomPhysNeuroBrain(agent, netPop.getNet(netPop.getIndexBestesNetz()).getId(), env.getRand(), netPop.getBestesNetz());
          agent.implantBrain(hirn);
          System.out.println("GELADEN: " + hirn.getNet().generateGenome(new DominikEncoding1()) + " Fitness: " + netPop.getFitness(netPop.getIndexBestesNetz()) + " ID: " + hirn.getNet().getId());


          for (int l = 1; l < popSize; l++) {
            agent = agenten.getAgent(l);

            env.removeAgent(l + 1);

          }

        }
        /*if(simZyk.getCurrentTime() == 100) {
          DomPhysAgent agent = agenten.getAgent(0);
          agent.setAgentShapeBIG();
        }*/
        
        //TEST
        /*if(simZyk.getCurrentTime() == 20000) {
          DomPhysAgent agent = agenten.getAgent(0);
          float x = 10;
          float y = 10;
          agent.adjustVelocity(new Vector2f(x,y));

        }
       
        if(simZyk.getCurrentTime() == 6000) {
          DomPhysAgent agent = agenten.getAgent(0);
          float x = 10;
          float y = 10;
          agent.adjustVelocity(new Vector2f(x,y));

        }
       
        if(simZyk.getCurrentTime() == 10000) {
          DomPhysAgent agent = agenten.getAgent(0);
          float x = 10;
          float y = 10;
          agent.adjustVelocity(new Vector2f(x,y));

        } */

      }
     
     

      /*if (saveLoad == 2) {
      for (int l = 1; l < popSize; l++) {
        DomPhysAgent agent = agenten.getAgent(l);

        agent.evaluate(simZyk);
      } */
     
     
      DomPhysAgent agent2 = agenten.getAgent(0);
      agent2.evaluate(simZyk);
     
      if(simZyk.getCurrentTime() % 50 == 0) {
    //System.out.println("FITNESS: " + agent2.getEvaluation() + " TICK: " + simZyk.getCurrentTime());
      }//System.out.println("Inputs: " + hirn.getNet().getInputs() + " Outputs: " + hirn.getNet().getOutputs());


      if (saveLoad == 0 || saveLoad == 1) {

        // Evaluierung jede Runde
        for (int l = 1; l < popSize + 1; l++) {

          DomPhysAgent agent = (DomPhysAgent) env.getAgent(l);
          if (saveLoad == 0 || saveLoad == 1) {
            //System.out.println(agent.getID() + "amLeben?: " + agent.getAmLeben() + "HIRN: " + agent.getBrain().getNet().getId());
            agent.evaluate(simZyk);
          }

          // Speichern und entfernen von toten Agenten

          int fitness = agent.getEvaluationInt();
          Color farbe = agent.getAgentColor();
          boolean lebend = agent.getAmLeben();

          /*if(l == 37) {
          System.out.println("Antrieb: " + agent.getActuatorWerte()[0] *80 + " / Drehung: " + agent.getActuatorWerte()[1] * 0.3);
        }*/

          if(!lebend) {

            DomPhysSparseNet netAlt = agent.getBrain().getNet();
            double minAbstand = agent.getMinAbstand();
            double maxAbstand = agent.getMaxAbstand();
            int geburt = agent.getGeburt();
            netPop.add(netAlt, fitness, minAbstand, maxAbstand, geburt);
            //System.out.println("Jetzt hinzufuegen: " + new DominikEncoding1().encode(hirn));

            env.removeAgent(l);

            // mutiertes Hirn
            DomPhysSparseNet netNeu = (DomPhysSparseNet) this.randVerteilung(netPop.getNetze(), netPop.getFitnesswerte(), env.getRand());

            DomPhysSparseNet mutNetNeu = netNeu.createMutatedOffspring(i, rand);

            DomPhysNeuroBrain hirnNeu = new DomPhysNeuroBrain(agent, i, env.getRand(), mutNetNeu);

            agent.implantBrain(hirnNeu);
           
            //Erkennung
              //if(i == 1131) {
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