void placeAgents()
{
simulationAgentEncapsulator mainAgentScript = null;
for (int i = 0; i < numberOfAgents; i++)
{
//Instantiate(agent, GeneratedPosition(), Quaternion.identity);
GameObject cloneAgent = Instantiate(prefab, GeneratedPosition(), Quaternion.identity) as GameObject;
cloneAgent.tag = "agent";
cloneAgent.name = "agent" + i;
int quarterNum = (int)numberOfAgents / 4;
mainAgentScript = cloneAgent.GetComponent <simulationAgentEncapsulator>();
if (i >= 0 && i < quarterNum)
{
mainAgentScript.assignedPersonality = simulationAgentEncapsulator.personalityType.Introverted;
mainAgentScript.assignedPersonalitySecond = simulationAgentEncapsulator.personalityTypeSecond.Cooperative;
}
if (i >= quarterNum && i < quarterNum * 2)
{
mainAgentScript.assignedPersonality = simulationAgentEncapsulator.personalityType.Introverted;
mainAgentScript.assignedPersonalitySecond = simulationAgentEncapsulator.personalityTypeSecond.Suspicious;
}
if (i >= quarterNum * 2 && i < quarterNum * 3)
{
mainAgentScript.assignedPersonality = simulationAgentEncapsulator.personalityType.Extroverted;
mainAgentScript.assignedPersonalitySecond = simulationAgentEncapsulator.personalityTypeSecond.Cooperative;
}
if (i >= quarterNum * 3 && i < quarterNum * 4)
{
mainAgentScript.assignedPersonality = simulationAgentEncapsulator.personalityType.Extroverted;
mainAgentScript.assignedPersonalitySecond = simulationAgentEncapsulator.personalityTypeSecond.Suspicious;
}
}
Debug.Log("Agents placed...");
}
void statistics()
{
GameObject a = GameObject.FindGameObjectWithTag("agent");
AgentBehaviourScript = a.GetComponent <AgentBehaviour>();
numberOfDirections = AgentBehaviourScript.numberOfDirections;
directionalFeatures = AgentBehaviourScript.stateMatrixFeatures.Length;
onedimensionalFeatures = AgentBehaviourScript.onedimensionalFeatures.Length;
GameObject[] agents = GameObject.FindGameObjectsWithTag("agent");
Debug.Log("agents " + agents.Length + " directional " + numberOfDirections * directionalFeatures + " onedimensional " + onedimensionalFeatures);
//Time.timeScale = 0;
//string buffer = "visited_info,unvisited_info,extraverted_agents,introverted_agents,total_agents,total_visited_info,total_unvisited_info,type" + System.Environment.NewLine;
string buffer = "vi,uvi,ea,ia,ca,sa,tae,tai,tca,tsa,tvi,tuvi,good,bad,score,type" + System.Environment.NewLine;
foreach (GameObject agent in agents)
{
AgentBehaviourScript = agent.GetComponent <AgentBehaviour>();
AgentEncapsulatorScript = agent.GetComponent <simulationAgentEncapsulator>();
double[] currentVector = AgentBehaviourScript.weightsVector;
List <GameObject> infopointsVisited = AgentBehaviourScript.infopointsVisited;
float totalScore = AgentBehaviourScript.totalScore;
int goodInfo = 0;
int badInfo = 0;
foreach (var infopoint in infopointsVisited)
{
infopointScript = infopoint.GetComponent <infopointDynamics> ();
if (infopointScript.disposition == infopointDynamics.possibleDispositions.Good)
{
goodInfo++;
}
else
{
badInfo++;
}
}
string personality = "";
if (AgentEncapsulatorScript.assignedPersonality == simulationAgentEncapsulator.personalityType.Extroverted)
{
personality = "E";
}
else
{
personality = "I";
}
if (AgentEncapsulatorScript.assignedPersonalitySecond == simulationAgentEncapsulator.personalityTypeSecond.Cooperative)
{
personality += "C";
}
else
{
personality += "S";
}
printArrayDouble(currentVector);
double bias = currentVector[currentVector.Length - 1];
Debug.Log(bias);
for (int i = 0; i < currentVector.Length; i++)
{
currentVector[i] = currentVector[i] - bias;
}
printArrayDouble(currentVector);
List <double> features = new List <double>();
for (int i = 0; i < directionalFeatures; i++)
{
//List<double> f = new List<double>();
double featureSum = 0f;
for (int j = 0; j < numberOfDirections; j++)
{
//Debug.Log(currentVector[j * directionalFeatures + i]);
featureSum += currentVector[j * directionalFeatures + i];
//f.Add(currentVector[j * directionalFeatures + i]);
//f.Add(j * directionalFeatures + i);
}
features.Add(featureSum / numberOfDirections);
}
for (int i = 0; i < onedimensionalFeatures; i++)
{
features.Add(currentVector[numberOfDirections * directionalFeatures + i]);
}
features.Add(goodInfo);
features.Add(badInfo);
features.Add(totalScore);
//Debug.Log(agent.name);
string featureBuffer = "";
int count = 0;
foreach (var feature in features)
{
count++;
if (count < features.Count)
{
featureBuffer += feature + ",";
}
else
{
featureBuffer += feature;
}
}
// if(!featureBuffer.Contains("0,0,0,0,0,0,0"))
buffer += featureBuffer + "," + personality + System.Environment.NewLine;
}
writeData(buffer);
}
private void Awake()
{
this.WarnIfMultipleInstances();
_unit = this.GetUnitFacade();
if (_unit == null)
{
Debug.LogError("WanderBehaviour requires a component that implements IMovable.");
this.enabled = false;
}
agentEncapsulatorScript = GetComponent <simulationAgentEncapsulator>();
minimumDistance = 60.0f;
rayAngle = 3;
fieldOFView = 25f;
goalFlag = false;
mainGrid = GridManager.instance.GetGrid(new Vector3(0, 0, 0));
//state function
range = 400;
interactRange = 20;
consumeReward = 0.5f;
socialReward = consumeReward;
visitedReward = (float)-consumeReward / 3;
refuseReward = (float)-socialReward / 3;
infopointsVisited = new List <GameObject>();
numberOfDirections = 8;
directionsState = new GameObject[numberOfDirections];
directionsVector = new float[numberOfDirections + 2];
directionsMatrix = new float[numberOfDirections, 2];
step = (float)1 / (numberOfDirections / 2);
//Debug.Log ("step: " + step);
/* rows of matrix - attributes that are perceived for each direction
*
* 0 - distance of the detected object - 0-1
*
* 1 - type of the detected object 1 - agent , 0 - info
*
* 2 - extraverted agent - 1, infopoint - 0
*
* 3 - introverted agent - 1 , infopoint - 0
*
*
* 0 - visited infopoints close - 0 - 1
*
* 1 - unvisited infopoints close - 0 -1
*
* 2 - extraverted agents close - 0 - 1
*
* 3 - intraverted agents close - 0 - 1
*
*/
stateMatrixFeatures = new float[4];
/* additional features
*
* 0 - total number of agents detected
*
* 1 - total number of visited infopoints detected
*
* 2 - total number of unvisited infopoints detected
*
* 3 - detecting agents personality type - 0 - introverted, 1 -extroverted
*
* 4 - detecting agent mood, positive 1, neutral 0.5, negative 0
*
*/
onedimensionalFeatures = new float[3];
vectorSize = numberOfDirections * stateMatrixFeatures.Length + onedimensionalFeatures.Length + 1; // + bias
previousfeaturesVector = new float[vectorSize];
weightsVector = new double[vectorSize];
matrixLength = stateMatrixFeatures.Length;
matrixSize = numberOfDirections * matrixLength;
int counter;
for (counter = 0; counter < weightsVector.Length; counter++)
{
weightsVector [counter] = 0f;
}
//Debug.Log (TestRange (-0.5f, -0.5f, -0.25f ));
for (int i = 0; i < numberOfDirections + 2; i++)
{
if (i <= numberOfDirections / 2)
{
//Debug.Log ("number " + i * step);
directionsVector [i] = i * step;
}
else
{
//Debug.Log ("number2 " + (i * step - ( 2 + step )));
directionsVector [i] = i * step - (2 + step);
}
//Debug.Log (i);
}
for (int i = 0; i < directionsMatrix.GetLength(0); i++)
{
if (i < numberOfDirections / 2)
{
directionsMatrix [i, 0] = directionsVector [i];
directionsMatrix [i, 1] = directionsVector [i + 1];
}
else
{
directionsMatrix [i, 0] = directionsVector [i + 1];
directionsMatrix [i, 1] = directionsVector [i + 2];
}
for (int j = 0; j < directionsMatrix.GetLength(1); j++)
{
float s = directionsMatrix[i, j];
//Debug.Log (i + "-"+ j + " " + s);
}
}
foreach (float item in directionsVector)
{
//Debug.Log (item);
}
}
