protected void setupVariables()
{
robots = new List <Robot>();
substrateDescription = new SubstrateDescription(substrateDescriptionFilename);
GenomeVisualizerForm.substrate = substrateDescription;
agentBrain = new AgentBrain(homogeneousTeam, numberRobots, substrateDescription, genome != null ? genome.Decode(null) : null, normalizeWeights, adaptableANN, modulatoryANN, multibrain, evolveSubstrate);
//if(homogeneousTeam)
//Console.WriteLine("inc:"+agentBrain.getBrain(0).InputNeuronCount);
loadEnvironments(this);
//agentsCollide=environment.agentsCollide;
//agentsVisible=environment.agentsVisible;
//Substrate sensor density
initializeRobots(agentBrain, environment, headingNoise, sensorNoise, effectorNoise, null);
setFitnessFunction(fitnessFunctionName);
setBehavioralCharacterization(behaviorCharacterizationName);
if (gridCollision)
{
collisionManager = new GridCollision();
}
else
{
collisionManager = new StandardCollision();
}
collisionManager.Initialize(environment, this, this.robots);
timeSteps = 0;
elapsed = 0;
}
public void init(int id, double nx, double ny, double dir,
AgentBrain agentBrain, Environment environment,
float sensorNoise, float effectorNoise, float headingNoise, float timeStep)
{
steps = 0;
this.id = id;
radius = defaultRobotSize();
location = new Point2D(nx, ny);
circle = new Circle2D(location, radius);
old_location = new Point2D(location);
heading = dir;
velocity = 0.0;
collide_last = false;
this.timeStep = timeStep;
this.environment = environment;
this.agentBrain = agentBrain;
this.sensorNoise = sensorNoise;
this.effectorNoise = effectorNoise;
this.headingNoise = headingNoise;
populateSensors();
if (environment.seed != -1)
{
rng = environment.rng; //new SharpNeatLib.Maths.FastRandom(environment.seed); //Utilities.random;
}
else
{
rng = environment.rng; //new SharpNeatLib.Maths.FastRandom();
}
}
public void init(int id, double nx, double ny, double dir,
AgentBrain agentBrain, Environment environment,
float sensorNoise, float effectorNoise, float headingNoise, float timeStep)
{
steps = 0;
this.id = id;
radius = defaultRobotSize();
location = new Point2D(nx, ny);
circle = new Circle2D(location, radius);
old_location = new Point2D(location);
heading = dir;
velocity = 0.0;
collide_last = false;
this.timeStep = timeStep;
this.environment = environment;
this.agentBrain = agentBrain;
this.sensorNoise = sensorNoise;
this.effectorNoise = effectorNoise;
this.headingNoise = headingNoise;
populateSensors();
if(environment.seed != -1)
rng=environment.rng; //new SharpNeatLib.Maths.FastRandom(environment.seed); //Utilities.random;
else
rng=environment.rng; //new SharpNeatLib.Maths.FastRandom();
}
protected void setupVariables()
{
//Console.WriteLine("setupVariables");
robots = new List <Robot>();
// Schrum: more special handling: Don't want to overwrite substrate in visual mode
if (!(fitnessFunction is FourTasksFitness))
{
substrateDescription = new SubstrateDescription(substrateDescriptionFilename);
}
agentBrain = new AgentBrain(homogeneousTeam, numberRobots, substrateDescription, genome != null ? genome.Decode(null) : null, normalizeWeights, adaptableANN, modulatoryANN, multibrain, numBrains, evolveSubstrate, preferenceNeurons, forcedSituationalPolicyGeometry);
//if(homogeneousTeam)
//Console.WriteLine("inc:"+agentBrain.getBrain(0).InputNeuronCount);
loadEnvironments(this);
//agentsCollide=environment.agentsCollide;
//agentsVisible=environment.agentsVisible;
//Substrate sensor density
initializeRobots(agentBrain, environment, headingNoise, sensorNoise, effectorNoise, null);
// Schrum: more special handling: Don't want to overwrite fitness function in visual mode
if (!(fitnessFunction is FourTasksFitness))
{
setFitnessFunction(fitnessFunctionName);
}
else // sufficient if FourTasks is already loaded
{
//Console.WriteLine("setupVariables: environmentName = " + environmentName);
((FourTasksFitness)fitnessFunction).setExperiment(this);
fitnessFunction.reset();
((FourTasksFitness)fitnessFunction).setupFitness(FourTasksFitness.environmentID(environmentName));
}
setBehavioralCharacterization(behaviorCharacterizationName);
if (gridCollision)
{
collisionManager = new GridCollision();
}
else
{
collisionManager = new StandardCollision();
}
collisionManager.Initialize(environment, this, this.robots);
timeSteps = 0;
elapsed = 0;
}
public virtual void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack x) { }
public virtual void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack x)
{
}
//TODO this could be put into a Formation class or something that takes an environment as input
public override void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack ip)
{
int num_bots;
//Set up robots.
//set up deltas for spacing the robots
double dx, dy;
if (overrideTeamFormation)
{
dx = Math.Cos(group_orientation / 180.0 * 3.14) * group_spacing;
dy = Math.Sin(group_orientation / 180.0 * 3.14) * group_spacing;
}
else
{
dx = Math.Cos(e.group_orientation / 180.0 * 3.14) * e.robot_spacing;
dy = Math.Sin(e.group_orientation / 180.0 * 3.14) * e.robot_spacing;
}
//record z-stack coordinates
//float zstack = -1.0f;
//float zdelta = 2.0f / (numberRobots - 1);
AgentBrain ab;
List <Robot> rbts;
double _timestep = 0.0;
if (ip == null)
{
ab = agentBrain;
rbts = robots;
num_bots = numberRobots;
_timestep = this.timestep;
}
else
{
ab = ip.agentBrain;
rbts = new List <Robot>();
ip.robots = rbts;
num_bots = ip.num_rbts;
_timestep = ip.timestep;
}
rbts.Clear();
int heading = overrideTeamFormation ? robot_heading : e.robot_heading;
//add robots in their formation according to environment
double nx, ny;
for (int num = 0; num < num_bots; num++)
{
Robot r = RobotModelFactory.getRobotModel(robotModelName);
r.rangefinderDensity = this.rangefinderSensorDensity;
//TODO: Make a variable that controls this
/*if (e.POIPosition.Count >= numberRobots)
* {
* nx = e.POIPosition[num].X;
* ny = e.POIPosition[num].Y;
* }
* else*/
{
nx = e.start_point.x + num * dx;
ny = e.start_point.y + num * dy;
}
r.init(num, nx, ny,
heading / 180.0 * 3.14, ab, e, sensorNoise, effectorNoise, headingNoise, (float)_timestep);
r.collisionPenalty = collisionPenalty;
ab.registerRobot(r);
//if (overrideDefaultSensorDensity)
// r.populateSensors(rangefinderSensorDensity);
//else
r.populateSensors(); //TODO populate sensors gets called multiple times. also in robot contructor
if (agentBrain.zcoordinates == null)
{
r.zstack = 0;
}
else
{
r.zstack = ab.zcoordinates[num];
}
//zstack;
rbts.Add(r);
//zstack += zdelta;
}
uint count = 0;
foreach (ISensor sensor in robots[0].sensors)
{
if (sensor is RangeFinder)
{
count++;
}
}
//Console.WriteLine("Range finder count : " + count);
//By convention the rangefinders are in layer zero so scale that layer
// Schrum: HOWEVER, if there are no rangefinders, then we do not want to do this.
// Schrum: Also disabled this when in the FourTasks domain, since it seems to cause problems.
if (count != 0 && !(this.fitnessFunction is FourTasksFitness))
{ // don't rescale rangefinders if there are none.
substrateDescription.setNeuronDensity(0, count, 1);
}
ab.updateInputDensity();
}
protected void setupVariables()
{
robots = new List<Robot>();
substrateDescription = new SubstrateDescription(substrateDescriptionFilename);
agentBrain = new AgentBrain(homogeneousTeam, numberRobots, substrateDescription, genome != null ? genome.Decode(null) : null, normalizeWeights, adaptableANN, modulatoryANN, multibrain, evolveSubstrate, dirComm);
//if(homogeneousTeam)
//Console.WriteLine("inc:"+agentBrain.getBrain(0).InputNeuronCount);
loadEnvironments(this);
//agentsCollide=environment.agentsCollide;
//agentsVisible=environment.agentsVisible;
//Substrate sensor density
initializeRobots(agentBrain, environment, headingNoise, sensorNoise, effectorNoise, null);
setFitnessFunction(fitnessFunctionName);
setBehavioralCharacterization(behaviorCharacterizationName);
if (gridCollision)
collisionManager = new GridCollision();
else
collisionManager = new StandardCollision();
collisionManager.Initialize(environment, this, this.robots);
timeSteps = 0;
elapsed = 0;
if (initialized)
foreach (Prey p in environment.preys)
{
p.reset();
}
preyCaught = 0;
}
//TODO this could be put into a Formation class or something that takes an environment as input
public override void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack ip)
{
int num_bots;
//Set up robots.
//set up deltas for spacing the robots
double dx, dy;
if (overrideTeamFormation)
{
dx = Math.Cos(group_orientation / 180.0 * 3.14) * group_spacing;
dy = Math.Sin(group_orientation / 180.0 * 3.14) * group_spacing;
}
else
{
dx = Math.Cos(e.group_orientation / 180.0 * 3.14) * e.robot_spacing;
dy = Math.Sin(e.group_orientation / 180.0 * 3.14) * e.robot_spacing;
}
//record z-stack coordinates
//float zstack = -1.0f;
//float zdelta = 2.0f / (numberRobots - 1);
AgentBrain ab;
List<Robot> rbts;
double _timestep=0.0;
if (ip == null)
{
ab = agentBrain;
rbts = robots;
num_bots = numberRobots;
_timestep = this.timestep;
}
else
{
ab = ip.agentBrain;
rbts = new List<Robot>();
ip.robots = rbts;
num_bots = ip.num_rbts;
_timestep=ip.timestep;
}
rbts.Clear();
int heading = overrideTeamFormation ? robot_heading : e.robot_heading;
//add robots in their formation according to environment
double nx, ny;
for (int num = 0; num < num_bots; num++)
{
Robot r = RobotModelFactory.getRobotModel(robotModelName);
r.rangefinderDensity = this.rangefinderSensorDensity;
//TODO: Make a variable that controls this
/*if (e.POIPosition.Count >= numberRobots)
{
nx = e.POIPosition[num].X;
ny = e.POIPosition[num].Y;
}
else*/
{
nx = e.start_point.x + num * dx;
ny = e.start_point.y + num * dy;
}
r.init(num, nx, ny,
heading / 180.0 * 3.14, ab, e, sensorNoise, effectorNoise, headingNoise, (float)_timestep);
r.collisionPenalty = collisionPenalty;
ab.registerRobot(r);
//if (overrideDefaultSensorDensity)
// r.populateSensors(rangefinderSensorDensity);
//else
r.populateSensors(); //TODO populate sensors gets called times. also in robot contructor
if (agentBrain.zcoordinates == null) r.zstack = 0;
else
r.zstack = ab.zcoordinates[num];
//zstack;
if (r is ModularRobot)
{
if (num == 1)
{
ModularRobot firstBot = (ModularRobot)rbts[0];
firstBot.initFirstBot((ModularRobot)r, e.robot_spacing);
rbts[0] = firstBot;
}
if (num != 0)
{
ModularRobot bot = (ModularRobot)r;
bot.initBot((ModularRobot)rbts[num - 1], e.robot_spacing);
r = bot;
}
}
rbts.Add(r);
//zstack += zdelta;
}
uint count = 0;
foreach (ISensor sensor in robots[0].sensors)
{
if (sensor is RangeFinder || sensor is PreySensor || sensor is TimeSensor)
{
count++;
}
}
//By convention the rangefinders are in layer zero so scale that layer
substrateDescription.setNeuronDensity(0, count, 1);
ab.updateInputDensity();
}
// Schrum2: Add extra enemy robot after deault robots
public override void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack ip)
{
// Debug:schrum2
//Console.WriteLine("Init Robots");
base.initializeRobots(agentBrain, e, headingNoise, sensorNoise, effectorNoise, ip);
enemies = new List <EnemyRobot>();
for (int i = 0; i < numEnemies; i++)
{
// schrum2: here is where the enemy robot is added
// Location of evolved robot is needed to track it
// Assumes that robot is in position 0 (problem?)
EnemyRobot r = new EnemyRobot(robots[0], flee);
enemies.Add(r);
double _timestep = 0.0;
if (ip == null)
{
_timestep = this.timestep;
}
else
{
_timestep = ip.timestep;
}
double nx = enemyX - i * enemyDeltaX;
double ny = enemyY - i * enemyDeltaY;
double h = 0;
// Alternative starting positions for enemies
if (enemiesSurround)
{
double evolvedX = robots[0].location.x;
double evolvedY = robots[0].location.y;
double radius = 200.0;
nx = evolvedX + radius * Math.Cos((i * 2.0 * Math.PI) / numEnemies);
ny = evolvedY + radius * Math.Sin((i * 2.0 * Math.PI) / numEnemies);
h = Math.PI + i * (2 * Math.PI / numEnemies);
}
r.init(robots.Count, // id is last position in list of robots
nx, ny, h, // starting position and heading
agentBrain, // Has evolved brain (to avoid NullPointers, etc), but should never actually use it (problem?)
e, sensorNoise, effectorNoise, headingNoise, (float)_timestep);
r.collisionPenalty = collisionPenalty;
// Only add enemy if it is not already present
if (robots.Count <= numEnemies) // Makes limiting assumption that this experiment will always be used with only one evolved bot and one enemy
{
robots.Add(r);
//Console.WriteLine("Added enemy to list: " + robots.Count);
}
// Required so that experiment works properly in both visual and non-visual mode
// (The non-visual mode takes the robots from the instance_pack instead of the experiment)
if (ip != null && ip.robots.Count <= numEnemies)
{
ip.robots.Add(r);
//Console.WriteLine("Added enemy to ip");
}
}
}
// Schrum2: Add extra enemy robot after deault robots
public override void initializeRobots(AgentBrain agentBrain, Environment e, float headingNoise, float sensorNoise, float effectorNoise, instance_pack ip)
{
// Debug:schrum2
//Console.WriteLine("Init Robots");
base.initializeRobots(agentBrain, e, headingNoise, sensorNoise, effectorNoise, ip);
enemies = new List<EnemyRobot>();
for (int i = 0; i < numEnemies; i++)
{
// schrum2: here is where the enemy robot is added
// Location of evolved robot is needed to track it
// Assumes that robot is in position 0 (problem?)
EnemyRobot r = new EnemyRobot(robots[0], flee);
enemies.Add(r);
double _timestep = 0.0;
if (ip == null)
{
_timestep = this.timestep;
}
else
{
_timestep = ip.timestep;
}
double nx = enemyX - i * enemyDeltaX;
double ny = enemyY - i * enemyDeltaY;
double h = 0;
// Alternative starting positions for enemies
if (enemiesSurround)
{
double evolvedX = robots[0].location.x;
double evolvedY = robots[0].location.y;
double radius = 200.0;
nx = evolvedX + radius*Math.Cos((i * 2.0 * Math.PI) / numEnemies);
ny = evolvedY + radius*Math.Sin((i * 2.0 * Math.PI) / numEnemies);
h = Math.PI + i * (2 * Math.PI / numEnemies);
}
r.init(robots.Count, // id is last position in list of robots
nx, ny, h, // starting position and heading
agentBrain, // Has evolved brain (to avoid NullPointers, etc), but should never actually use it (problem?)
e, sensorNoise, effectorNoise, headingNoise, (float)_timestep);
r.collisionPenalty = collisionPenalty;
// Only add enemy if it is not already present
if (robots.Count <= numEnemies) // Makes limiting assumption that this experiment will always be used with only one evolved bot and one enemy
{
robots.Add(r);
//Console.WriteLine("Added enemy to list: " + robots.Count);
}
// Required so that experiment works properly in both visual and non-visual mode
// (The non-visual mode takes the robots from the instance_pack instead of the experiment)
if (ip != null && ip.robots.Count <= numEnemies)
{
ip.robots.Add(r);
//Console.WriteLine("Added enemy to ip");
}
}
}
