Java tutorial
/* * The Bio-inspired Leadership Toolkit is a set of tools used to * simulate the emergence of leaders in multi-agent systems. * Copyright (C) 2014 Southern Nazarene University * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ package edu.snu.leader.simple; // Imports import edu.snu.jyperneat.core.NeatIndividual; import edu.snu.jyperneat.core.Network; import edu.snu.leader.util.CrossValidationFitness; import edu.snu.leader.util.IndividualDescriber; import org.apache.commons.lang.Validate; import org.apache.log4j.Logger; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.FileOutputStream; import java.io.IOException; import java.io.ObjectInputStream; import java.io.ObjectOutputStream; import ec.EvolutionState; import ec.Individual; import ec.Problem; import ec.simple.SimpleProblemForm; import ec.util.MersenneTwisterFast; import ec.util.Parameter; /** * SimpleDevelopmentProblem * * TODO Class description * * @author Brent Eskridge * @version $Revision$ ($Author$) */ public class SimpleDevelopmentProblem extends Problem implements SimpleProblemForm, IndividualDescriber { /** Default serial version UID */ private static final long serialVersionUID = 1L; /** Our logger */ private static final Logger _LOG = Logger.getLogger(SimpleDevelopmentProblem.class.getName()); private enum PredationInputType { ACCURATE { @Override double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random) { return predationLevel; } }, NOISY { @Override double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random) { double noisyPredationLevel = predationLevel + noiseMultiplier * random.nextGaussian(); return Math.min(1.0, Math.max(0.0, noisyPredationLevel)); } }, RANDOM { @Override double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random) { return random.nextDouble(); } }, ZERO { @Override double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random) { return 0.0; } }, OFF { @Override double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random) { return -1.0; } }; abstract double calculateInput(float predationLevel, float noiseMultiplier, MersenneTwisterFast random); }; /** The bias node's name */ private static final String _BIAS_NODE_NAME = "Bias"; /** The predation level node's name */ private static final String _PREDATION_NODE_NAME = "Predation"; /** The energy node name */ private static final String _ENERGY_NODE_NAME = "Energy"; /** The maturation node name */ private static final String _MATURATION_NODE_NAME = "Maturation"; /** The other individual's activity node name */ private static final String _OTHER_ACTIVITY_NODE_NAME = "Other-Activity"; /** The sensor failure node name */ private static final String _SENSOR_FAILURE_NODE_NAME = "Sensor-Failure"; /** The output node's name */ private static final String _OUTPUT_NODE_NAME = "Output"; /** The bias input value */ private static final double _BIAS_INPUT_VALUE = 0.03; /** The minimum amount of energy for survival of a timestep */ private static final float _MIN_ENERGY_THRESHOLD = 0.001f; /** The description format */ private static final String _DESCRIPTION_FORMAT = "%1$4.2f %2$4.2f %3$4.2f %4$4.2f %5$4.2f"; /** Parameter key for the maximum number of timesteps */ private static final String _MAX_TIMESTEPS_KEY = "max-timesteps"; /** Parameter key for the minimum energy consumed per timestep */ private static final String _MIN_ENERGY_CONSUMED_PER_TIMESTEP_KEY = "min-energy-consumed-per-timestep"; /** Parameter key for the multiplier multiplied by the activity level to * compute energy loss */ private static final String _ACTIVITY_ENERGY_LOSS_MULTIPLIER_KEY = "activity-energy-loss-multiplier"; /** Parameter key for the maturation energy threshold */ private static final String _MATURATION_ENERGY_THRESHOLD_KEY = "maturation-energy-threshold"; /** Parameter key for the amount of energy consumed per timestep by * maturation */ private static final String _MATURATION_ENERGY_CONSUMED_PER_TIMESTEP_KEY = "maturation-energy-consumed-per-timestep"; /** Parameter key for the multiplier multiplied by the activity level to * compute energy gain */ private static final String _ENERGY_GAIN_MULTIPLIER_KEY = "energy-gain-multiplier"; /** Parameter key for the initial energy level */ private static final String _INITIAL_ENERGY_LEVEL_KEY = "initial-energy-level"; /** Parameter key for the number of evaluations to perform per network */ private static final String _EVALUATION_COUNT_KEY = "evaluation-count"; /** Parameter key for the number of evaluations to perform using the * alternate predation input type */ private static final String _ALT_EVALUATION_COUNT_KEY = "alt-evaluation-count"; /** Parameter key for the number of steps to use for describing a network */ private static final String _DESCRIPTION_STEP_COUNT_KEY = "description-step-count"; /** Parameter key for the type of predation input */ private static final String _PREDATION_INPUT_TYPE_KEY = "predation-input-type"; /** Parameter key for the alternate type of predation input */ private static final String _ALT_PREDATION_INPUT_TYPE_KEY = "alt-predation-input-type"; /** Parameter key for predation level noise multiplier */ private static final String _PREDATION_NOISE_MULTIPLIER_KEY = "predation-noise-multiplier"; /** Parameter key for the other's network file */ private static final String _OTHER_NETWORK_FILE = "other-network-file"; /** Parameter key for the type of predation input for the other ind */ private static final String _OTHER_PREDATION_INPUT_TYPE_KEY = "other-predation-input-type"; /** Parameter key for the alternate type of predation input for the other ind */ private static final String _ALT_OTHER_PREDATION_INPUT_TYPE_KEY = "alt-other-predation-input-type"; /** Parameter key for the other's predation level noise multiplier */ private static final String _OTHER_PREDATION_NOISE_MULTIPLIER_KEY = "other-predation-noise-multiplier"; /** The maximum number of timesteps */ private int _maxTimesteps = 0; /** The energy consumed per timestep */ private float _minEnergyConsumedPerTimestep = 0.0f; /** The multiplier multiplied by the activity level to compute energy loss */ private float _activityEnergyLossMultiplier = 0.0f; /** The energy threshold for maturation to occur */ private float _maturationEnergyThreshold = 0.0f; /** The amount of energy consumed per timestep by maturation */ private float _maturationEnergyConsumedPerTimestep = 0.0f; /** The multiplier multiplied by the activity level to compute energy gain */ private float _energyGainMultiplier = 0.0f; /** The initial energy level of the individual */ private float _initialEnergyLevel = 0.0f; /** The number of evaluations to perform per network */ private int _evaluationCount = 0; /** The number of evaluations to perform using the alternation predation * input type */ private int _altEvaluationCount = 0; /** The number of steps to use for describing a network */ private int _descriptionStepCount = 0; /** The type of predation input */ private PredationInputType _predationInputType = PredationInputType.ACCURATE; /** The alternate type of predation input */ private PredationInputType _altPredationInputType = PredationInputType.ACCURATE; /** The predation level noise multiplier */ private float _predationNoiseMultiplier = 0.0f; /** The other individual's network */ private Network _otherNetwork = null; /** The type of predation input for the other individual */ private PredationInputType _otherPredationInputType = PredationInputType.ACCURATE; /** The alternate type of predation input for the other individual */ private PredationInputType _altOtherPredationInputType = PredationInputType.ACCURATE; /** The other individual's predation level noise multiplier */ private float _otherPredationNoiseMultiplier = 0.0f; /** * Sets up the object by reading it from the parameters stored in * state, built off of the parameter base base. * * @param state * @param base * @see ec.Problem#setup(ec.EvolutionState, ec.util.Parameter) */ @Override public void setup(EvolutionState state, Parameter base) { _LOG.trace("Entering setup( state, base )"); // Call the superclass implementation super.setup(state, base); // Get the maximum number of timesteps Validate.isTrue(state.parameters.exists(base.push(_MAX_TIMESTEPS_KEY)), "Max timesteps parameter not found"); _maxTimesteps = state.parameters.getInt(base.push(_MAX_TIMESTEPS_KEY), null); _LOG.info("Using maxTimesteps=[" + _maxTimesteps + "]"); // Get the energy consumed per timestep Validate.isTrue(state.parameters.exists(base.push(_MIN_ENERGY_CONSUMED_PER_TIMESTEP_KEY)), "Energy consumed per timestep not found"); _minEnergyConsumedPerTimestep = state.parameters.getFloat(base.push(_MIN_ENERGY_CONSUMED_PER_TIMESTEP_KEY), null); _LOG.info("Using minEnergyConsumedPerTimestep=[" + _minEnergyConsumedPerTimestep + "]"); // Get the activity energy loss multiplier Validate.isTrue(state.parameters.exists(base.push(_ACTIVITY_ENERGY_LOSS_MULTIPLIER_KEY)), "Energy consumed per timestep not found"); _activityEnergyLossMultiplier = state.parameters.getFloat(base.push(_ACTIVITY_ENERGY_LOSS_MULTIPLIER_KEY), null); _LOG.info("Using activityEnergyLossMultiplier=[" + _activityEnergyLossMultiplier + "]"); // Get the maturation energy threshold Validate.isTrue(state.parameters.exists(base.push(_MATURATION_ENERGY_THRESHOLD_KEY)), "Maturation energy threshold not found"); _maturationEnergyThreshold = state.parameters.getFloat(base.push(_MATURATION_ENERGY_THRESHOLD_KEY), null); _LOG.info("Using maturationEnergyThreshold=[" + _maturationEnergyThreshold + "]"); // Get the maturation energy consumed per timestep Validate.isTrue(state.parameters.exists(base.push(_MATURATION_ENERGY_CONSUMED_PER_TIMESTEP_KEY)), "Maturation energy consumed per timestep not found"); _maturationEnergyConsumedPerTimestep = state.parameters .getFloat(base.push(_MATURATION_ENERGY_CONSUMED_PER_TIMESTEP_KEY), null); _LOG.info("Using maturationEnergyConsumedPerTimestep=[" + _maturationEnergyConsumedPerTimestep + "]"); // Get the maturation energy threshold Validate.isTrue(state.parameters.exists(base.push(_ENERGY_GAIN_MULTIPLIER_KEY)), "Energy gain multiplier not found"); _energyGainMultiplier = state.parameters.getFloat(base.push(_ENERGY_GAIN_MULTIPLIER_KEY), null); _LOG.info("Using energyGainMultiplier=[" + _energyGainMultiplier + "]"); // Get the initial energy level Validate.isTrue(state.parameters.exists(base.push(_INITIAL_ENERGY_LEVEL_KEY)), "Energy gain multiplier not found"); _initialEnergyLevel = state.parameters.getFloat(base.push(_INITIAL_ENERGY_LEVEL_KEY), null); _LOG.info("Using initialEnergyLevel=[" + _initialEnergyLevel + "]"); // Get the evaluation count Validate.isTrue(state.parameters.exists(base.push(_EVALUATION_COUNT_KEY)), "Evaluation count not found"); _evaluationCount = state.parameters.getInt(base.push(_EVALUATION_COUNT_KEY), null); _LOG.info("Using evaluationCount=[" + _evaluationCount + "]"); /* Get the number of evaluations to perform using the alternation * predation input type */ _altEvaluationCount = state.parameters.getInt(base.push(_ALT_EVALUATION_COUNT_KEY), null, -1); _LOG.info("Using altEvaluationCount=[" + _altEvaluationCount + "]"); // Get the initial energy level Validate.isTrue(state.parameters.exists(base.push(_DESCRIPTION_STEP_COUNT_KEY)), "Description step count not found"); _descriptionStepCount = state.parameters.getInt(base.push(_DESCRIPTION_STEP_COUNT_KEY), null); _LOG.info("Using descriptionStepCount=[" + _descriptionStepCount + "]"); // Get the predation input type Validate.isTrue(state.parameters.exists(base.push(_PREDATION_INPUT_TYPE_KEY)), "Predation input type not found"); String predationInputType = state.parameters.getString(base.push(_PREDATION_INPUT_TYPE_KEY), null); _predationInputType = PredationInputType.valueOf(predationInputType.toUpperCase().trim()); Validate.notNull(_predationInputType, "Unknown predation input type [" + predationInputType + "]"); _LOG.info("Using predationInputType=[" + _predationInputType + "]"); // Get the alternate predation input type String altPredationInputType = state.parameters.getString(base.push(_ALT_PREDATION_INPUT_TYPE_KEY), null); if (null != altPredationInputType) { _altPredationInputType = PredationInputType.valueOf(altPredationInputType.toUpperCase().trim()); Validate.notNull(_altPredationInputType, "Unknown alternate predation input type [" + _altPredationInputType + "]"); _LOG.info("Using altPredationInputType=[" + _altPredationInputType + "]"); } // Get the predation noise level multiplier _predationNoiseMultiplier = state.parameters.getFloat(base.push(_PREDATION_NOISE_MULTIPLIER_KEY), null, 0.0f); _LOG.info("Using predationNoiseMultiplier=[" + _predationNoiseMultiplier + "]"); // Get the other's serialized network file (if specified) if (state.parameters.exists(base.push(_OTHER_NETWORK_FILE))) { String otherNetworkFile = state.parameters.getString(base.push(_OTHER_NETWORK_FILE), null); // Deserialize the network file try { ObjectInputStream in = new ObjectInputStream(new FileInputStream(otherNetworkFile)); Object obj = in.readObject(); in.close(); _otherNetwork = (Network) obj; } catch (Exception e) { _LOG.error("Unable to load other's serialized network from [" + otherNetworkFile + "]", e); System.err.println("Unable to load other's serialized network from [" + otherNetworkFile + "]"); e.printStackTrace(); System.exit(1); } // Get the predation input type Validate.isTrue(state.parameters.exists(base.push(_OTHER_PREDATION_INPUT_TYPE_KEY)), "Other predation input type not found"); String otherPredationInputType = state.parameters.getString(base.push(_OTHER_PREDATION_INPUT_TYPE_KEY), null); _otherPredationInputType = PredationInputType.valueOf(otherPredationInputType.toUpperCase().trim()); Validate.notNull(_otherPredationInputType, "Unknown other predation input type [" + otherPredationInputType + "]"); _LOG.info("Using otherPredationInputType=[" + _otherPredationInputType + "]"); // Get the alternate predation input type String otherAltPredationInputType = state.parameters .getString(base.push(_ALT_OTHER_PREDATION_INPUT_TYPE_KEY), null); if (null != otherAltPredationInputType) { _altOtherPredationInputType = PredationInputType .valueOf(otherAltPredationInputType.toUpperCase().trim()); Validate.notNull(otherAltPredationInputType, "Unknown alternate other predation input type [" + otherAltPredationInputType + "]"); _LOG.info("Using altOtherPredationInputType=[" + _altOtherPredationInputType + "]"); } // Get the noise multiplier _otherPredationNoiseMultiplier = state.parameters .getFloat(base.push(_OTHER_PREDATION_NOISE_MULTIPLIER_KEY), null, 0.0f); _LOG.info("Using otherPredationNoiseMultiplier=[" + _otherPredationNoiseMultiplier + "]"); } _LOG.trace("Leaving setup( state, base )"); } /** * Evaluates the individual in ind, if necessary (perhaps not * evaluating them if their evaluated flags are true), and sets * their fitness appropriately. * * @param state * @param ind * @param subpopulation * @param threadnum * @see ec.simple.SimpleProblemForm#evaluate(ec.EvolutionState, ec.Individual, int, int) */ @Override public void evaluate(EvolutionState state, Individual ind, int subpopulation, int threadnum) { // Has the individual already been evaluated? if (ind.evaluated) { // Yup, bail out early return; } // Is it the correct type of individual? if (!(ind instanceof NeatIndividual)) { // Nope, complain _LOG.error("Individual is not of correct type [" + ind.getClass().getCanonicalName() + "]"); state.output.fatal("Individual is not the correct type"); } // Cast it to the correct type NeatIndividual neatInd = (NeatIndividual) ind; // Build the network Network network = neatInd.createPhenotype(); // Evaluate the network MersenneTwisterFast random = state.random[threadnum]; float[] trainFitness = new float[_evaluationCount]; for (int i = 0; i < _evaluationCount; i++) { trainFitness[i] = evaluateNetwork(network, random, (i < _altEvaluationCount)); network.reinitialize(random); } ((CrossValidationFitness) ind.fitness).setTrainingResults(trainFitness); // Average them to get the total evolutionary fitness float evoFitness = 0.0f; for (int i = 0; i < trainFitness.length; i++) { evoFitness += trainFitness[i]; } evoFitness /= trainFitness.length; if (evoFitness > 0.9999f) { _LOG.debug("PERFECT!!"); } // Set the individual's fitness ((CrossValidationFitness) ind.fitness).setFitness(state, evoFitness, false); // Mark the individual as evaluated neatInd.evaluated = true; } /** * Returns a description of the specified individual using the specified * line prefix. * * @param ind The individual to describe * @param prefix The prefix for every line in the description * @param statDir The statistics directory * @return A description of the individual * @see edu.snu.leader.util.IndividualDescriber#describe(ec.Individual, java.lang.String) */ @Override public String describe(Individual ind, String prefix, String statDir) { _LOG.trace("Entering describe( ind, prefix )"); // Is it the correct type of individual? if (!(ind instanceof NeatIndividual)) { // Nope, complain _LOG.error("Individual is not of correct type [" + ind.getClass().getCanonicalName() + "]"); throw new IllegalArgumentException("Individual is not of correct type"); } // Cast it to the correct type NeatIndividual neatInd = (NeatIndividual) ind; // Build the network Network network = neatInd.createPhenotype(); // Serialize the network String serializeFilename = "network-" + buildDescriptionFilenameBase(prefix) + "-" + System.getProperty("hostname") + "-runid-" + System.getProperty("run-id", "default") + ".ser"; try { ObjectOutputStream objOut = new ObjectOutputStream( new FileOutputStream(new File(statDir, serializeFilename))); objOut.writeObject(network); objOut.close(); } catch (FileNotFoundException fnfe) { _LOG.error("Unable to open network serialization file [" + serializeFilename + "]", fnfe); return "ERROR"; } catch (IOException ioe) { _LOG.error("Unable to open network serialization file [" + serializeFilename + "]", ioe); return "ERROR"; } // // Build the description filename // String filename = "results-" // + buildDescriptionFilenameBase( prefix ) // + "-" // + System.getProperty( "hostname" ) // + "-runid-" // + System.getProperty( "run-id", "default" ) // + ".dat"; // // // Open the file // PrintWriter writer = null; // try // { // writer = new PrintWriter( new BufferedWriter( // new FileWriter( new File( statDir, filename ) ) ) ); // } // catch( IOException ioe ) // { // _LOG.error( "Unable to open description file [" // + filename // + "]", // ioe ); // return "ERROR"; // } // // // Write some header information // writer.println( "# 1: Predation level" ); // writer.println( "# 2: Energy level" ); // writer.println( "# 3: Maturation level" ); // writer.println( "# 4: Other's activity level" ); // writer.println( "# 5: Activity level" ); // // // Build an array of all the possible predation levels // float[] predationLevels = new float[ _descriptionStepCount ]; // if( PredationInputType.OFF.equals( _predationInputType) // || PredationInputType.OFF.equals( _altPredationInputType ) ) // { // predationLevels = new float[ _descriptionStepCount + 1]; // predationLevels[_descriptionStepCount] = -1.0f; // } // float[] energyLevels = new float[ _descriptionStepCount ]; // float[] maturationLevels = new float[ _descriptionStepCount ]; // float[] otherActivityLevels = new float[ _descriptionStepCount ]; // if( PredationInputType.OFF.equals( _otherPredationInputType) // || PredationInputType.OFF.equals( _altOtherPredationInputType ) ) // { // otherActivityLevels = new float[ _descriptionStepCount + 1]; // otherActivityLevels[_descriptionStepCount] = -1.0f; // } // float stepSize = 1.0f / (_descriptionStepCount - 1); // for( int i = 0; i < _descriptionStepCount; ++i ) // { // float value = i * stepSize; // predationLevels[i] = value; // energyLevels[i] = value; // maturationLevels[i] = value; // otherActivityLevels[i] = value; // } // // // Iterate through all the possible states // MersenneTwisterFast random = new MersenneTwisterFast(); // for( int predationIdx = 0; predationIdx < predationLevels.length; // ++predationIdx ) // { // for( int energyIdx = 0; energyIdx < energyLevels.length; // ++energyIdx ) // { // for( int maturationIdx = 0; // maturationIdx < maturationLevels.length; // ++maturationIdx ) // { // for( int otherActivityIdx = 0; // otherActivityIdx < otherActivityLevels.length; // ++otherActivityIdx ) // { // // Send the inputs to the network // network.reinitialize( random ); // network.setValue( _BIAS_NODE_NAME, _BIAS_INPUT_VALUE ); // network.setValue( _PREDATION_NODE_NAME, // predationLevels[predationIdx] ); // network.setValue( _ENERGY_NODE_NAME, // energyLevels[energyIdx] ); // network.setValue( _MATURATION_NODE_NAME, // maturationLevels[maturationIdx] ); // network.setValue( _OTHER_ACTIVITY_NODE_NAME, // otherActivityLevels[otherActivityIdx] ); // // // Update the network // network.update(); // // // Get the output (i.e., activity of the individual) // float activity = (float) network.getValue( _OUTPUT_NODE_NAME ); // // // Write out all the details // writer.format( _DESCRIPTION_FORMAT, // predationLevels[predationIdx], // energyLevels[energyIdx], // maturationLevels[maturationIdx], // otherActivityLevels[otherActivityIdx], // activity ); // writer.println( "" ); // } // } // } // } // // // Close the file // writer.close(); _LOG.trace("Leaving describe( ind, prefix )"); return prefix + "file = " + serializeFilename + NEWLINE; } /** * TODO Method description * * @param ind * @param state * @param subpopulation * @param threadnum * @param log * @param verbosity * @see ec.simple.SimpleProblemForm#describe(ec.Individual, ec.EvolutionState, int, int, int, int) */ @Override public void describe(Individual ind, EvolutionState state, int subpopulation, int threadnum, int log, int verbosity) { throw new RuntimeException("NOT YET IMPLEMENTED"); } /** * Evaluates the network in the maturation simulation * * @param network * @param random * @param useAlt * @return */ private float evaluateNetwork(Network network, MersenneTwisterFast random, boolean useAlt) { // Which predation types do we use? PredationInputType thisPredationType = _predationInputType; PredationInputType otherPredationType = _otherPredationInputType; if (useAlt) { thisPredationType = _altPredationInputType; otherPredationType = _altOtherPredationInputType; } //_LOG.warn( " OtherPredationType is: " + otherPredationType.name() ); _LOG.debug("thisPredationType=[" + thisPredationType + "] otherPredationType=[" + otherPredationType + "]"); // Compute a random offset for the predation level float predationLevelOffset = random.nextFloat(); // Create some variables needed for the simulation float maturationLevel = 0.0f; float energyLevel = _initialEnergyLevel; float predationLevel = 0.0f; // Run the simulation for (int i = 0; i < _maxTimesteps; ++i) { // Calculate the predation level predationLevel = calculatePredationLevel(i, predationLevelOffset); // Send the inputs to the network network.reinitialize(random); network.setValue(_BIAS_NODE_NAME, _BIAS_INPUT_VALUE); network.setValue(_ENERGY_NODE_NAME, energyLevel); network.setValue(_MATURATION_NODE_NAME, maturationLevel); // Send the appropriate predation input network.setValue(_PREDATION_NODE_NAME, thisPredationType.calculateInput(predationLevel, _predationNoiseMultiplier, random)); // Send the status of our predation sensor float sensorFailure = 0.0f; if (PredationInputType.RANDOM.equals(thisPredationType)) { sensorFailure = 1.0f; } network.setValue(_SENSOR_FAILURE_NODE_NAME, sensorFailure); // Send the appropriate input from the other's actions if (null == _otherNetwork) { network.setValue(_OTHER_ACTIVITY_NODE_NAME, 0.0); } else if (PredationInputType.OFF.equals(otherPredationType)) { network.setValue(_OTHER_ACTIVITY_NODE_NAME, -1.0f); } else { // Find out what the other individual will do _otherNetwork.reinitialize(random); _otherNetwork.setValue(_BIAS_NODE_NAME, _BIAS_INPUT_VALUE); _otherNetwork.setValue(_ENERGY_NODE_NAME, energyLevel); _otherNetwork.setValue(_MATURATION_NODE_NAME, maturationLevel); _otherNetwork.setValue(_PREDATION_NODE_NAME, otherPredationType.calculateInput(predationLevel, _otherPredationNoiseMultiplier, random)); _otherNetwork.update(); double otherActivity = _otherNetwork.getValue(_OUTPUT_NODE_NAME); // Send it to the current individual's network network.setValue(_OTHER_ACTIVITY_NODE_NAME, otherActivity); } // Update the network network.update(); // Get the output (i.e., activity of the individual) float activity = (float) network.getValue(_OUTPUT_NODE_NAME); // Did the activity result in capture? if (isCaptured(activity, predationLevel, random)) { // Yup, bail here if (_LOG.isDebugEnabled()) { _LOG.debug("CAPTURED: time[" + i + "] predationLevel=[" + predationLevel // + "*****" + "] predationLevelOffset=[" + predationLevelOffset + "] energyLevel=[" + energyLevel + "] maturationLevel=[" + maturationLevel + "] activity=[" + activity + "] sensorFailure=[" + sensorFailure + "]"); } break; } // Nope, how much energy was gained? energyLevel += _energyGainMultiplier * activity; // Compute how much energy was used by the activity energyLevel -= (_minEnergyConsumedPerTimestep + activity * _activityEnergyLossMultiplier); // Is there any left over for maturation?? if (energyLevel > _maturationEnergyThreshold) { // Yes, calculate how much energy was used float maturationEnergy = Math.min(_maturationEnergyConsumedPerTimestep, (energyLevel - _maturationEnergyThreshold)); energyLevel -= maturationEnergy; maturationLevel += maturationEnergy; _LOG.debug("Matured [" + maturationEnergy + "] amount"); } // Ensure the maximum energy isn't exceeded energyLevel = Math.min(1.0f, energyLevel); // Does the individual have enough energy to survive? if (energyLevel < _MIN_ENERGY_THRESHOLD) { // Nope if (_LOG.isDebugEnabled()) { _LOG.debug("STARVED: time[" + i + "] predationLevel=[" + predationLevel // + "*****" + "] predationLevelOffset=[" + predationLevelOffset + "] energyLevel=[" + energyLevel + "] maturationLevel=[" + maturationLevel + "] activity=[" + activity + "] sensorFailure=[" + sensorFailure + "]"); } break; } // Did the individual reach full maturation? if (maturationLevel >= 1.0f) { // Yup maturationLevel = 1.0f; if (_LOG.isDebugEnabled()) { _LOG.debug("FULL MATURATION: time[" + i + "] predationLevel=[" // + predationLevel + "*****" + "] predationLevelOffset=[" + predationLevelOffset + "] energyLevel=[" + energyLevel + "] maturationLevel=[" + maturationLevel + "] activity=[" + activity + "] sensorFailure=[" + sensorFailure + "]"); } break; } // Log the state and activity if needed if (_LOG.isDebugEnabled()) { _LOG.debug("EVADED: time[" + i + "] predationLevel=[" + predationLevel // + "*****" + "] predationLevelOffset=[" + predationLevelOffset + "] energyLevel=[" + energyLevel + "] maturationLevel=[" + maturationLevel + "] activity=[" + activity + "] sensorFailure=[" + sensorFailure + "]"); } } float fitness = maturationLevel; if (Math.abs(fitness - 1.0f) > 0.001) { fitness *= energyLevel; } return maturationLevel; } /** * Calculates the current predation level * * @param timestep * @param offset * @return */ private float calculatePredationLevel(int timestep, float offset) { double period = 80.0; double sineParameter = Math.PI * (offset + (timestep * 2.0f) / period); return (float) Math.pow(((Math.sin(sineParameter) + 1.0) / 2.0), 2); } /** * Determines if the individual was captures * * @param activityLevel * @param predationLevel * @param random * @return */ private boolean isCaptured(float activityLevel, float predationLevel, MersenneTwisterFast random) { return (random.nextFloat() < (activityLevel * predationLevel)); } private String buildDescriptionFilenameBase(String prefix) { String filenameBase = prefix.replaceAll("\\[", "-"); filenameBase = filenameBase.replaceAll("\\.", "-"); filenameBase = filenameBase.replaceAll("\\]", ""); if (filenameBase.endsWith("-")) { filenameBase = filenameBase.substring(0, filenameBase.length() - 1); } return filenameBase; } }