static void SerializeDriveComponent()
{
World.LoggingLevel = TraceLevel.Warning;
Agent John = World.NewAgent("John");
BPNetwork net;
FoodDrive foodDr = AgentInitializer.InitializeDrive(John, FoodDrive.Factory, .5);;
if (load && File.Exists(componentLoadFile))
{
Console.WriteLine("Deserializing the drive component");
SerializationPlugin.DeserializeDriveComponent(foodDr, componentLoadFile, out net);
}
else
{
Console.WriteLine("Initializing the drive component");
net = AgentInitializer.InitializeDriveComponent(foodDr, BPNetwork.Factory);
net.Input.AddRange(Drive.GenerateTypicalInputs(foodDr));
net.Parameters.LEARNING_RATE = .2;
net.Parameters.MOMENTUM = .05;
foodDr.Commit(net);
}
John.Commit(foodDr);
DoTraining(net, foodDr);
Console.WriteLine("Serializing the drive component");
SerializationPlugin.Serialize(net, componentLoadFile);
John.Die();
}
static void SerializeWorld()
{
Agent John;
BPNetwork net;
FoodDrive foodDr;
if (load && File.Exists(worldLoadFile))
{
Console.WriteLine("Deserializing the world");
SerializationPlugin.DeserializeWorld(worldLoadFile);
John = World.GetAgent("John");
foodDr = (FoodDrive)John.GetInternals(Agent.InternalContainers.DRIVES).First();
net = (BPNetwork)foodDr.DriveComponent;
}
else
{
Console.WriteLine("Initializing the world");
World.LoggingLevel = TraceLevel.Warning;
John = World.NewAgent("John");
foodDr = AgentInitializer.InitializeDrive(John, FoodDrive.Factory, .5);
net = AgentInitializer.InitializeDriveComponent(foodDr, BPNetwork.Factory);
net.Input.AddRange(Drive.GenerateTypicalInputs(foodDr));
net.Parameters.LEARNING_RATE = .2;
net.Parameters.MOMENTUM = .05;
foodDr.Commit(net);
John.Commit(foodDr);
}
DoTraining(net, foodDr);
Console.WriteLine("Serializing the world");
SerializationPlugin.SerializeWorld(worldLoadFile);
John.Die();
}
public static void InitializeAgent(Groups gr)
{
Participant = World.NewAgent();
BPNetwork idn = AgentInitializer.InitializeImplicitDecisionNetwork(Participant, BPNetwork.Factory);
idn.Input.AddRange(dvs);
idn.Output.AddRange(acts);
Participant.Commit(idn);
foreach (DeclarativeChunk t in tools)
{
RefineableActionRule a = AgentInitializer.InitializeActionRule(Participant, RefineableActionRule.Factory, World.GetActionChunk("Tool"));
foreach (DimensionValuePair dv in t)
{
a.GeneralizedCondition.Add(dv, true);
}
Participant.Commit(a);
}
foreach (DeclarativeChunk g in guns)
{
RefineableActionRule a = AgentInitializer.InitializeActionRule(Participant, RefineableActionRule.Factory, World.GetActionChunk("Gun"));
foreach (DimensionValuePair dv in g)
{
a.GeneralizedCondition.Add(dv, true);
}
Participant.Commit(a);
}
Participant.ACS.Parameters.PERFORM_RER_REFINEMENT = false;
Participant.ACS.Parameters.PERFORM_DELETION_BY_DENSITY = false;
Participant.ACS.Parameters.FIXED_BL_LEVEL_SELECTION_MEASURE = 1;
Participant.ACS.Parameters.FIXED_RER_LEVEL_SELECTION_MEASURE = 1;
Participant.ACS.Parameters.FIXED_IRL_LEVEL_SELECTION_MEASURE = 0;
Participant.ACS.Parameters.FIXED_FR_LEVEL_SELECTION_MEASURE = 0;
Participant.ACS.Parameters.B = 1;
HonorDrive honor = AgentInitializer.InitializeDrive(Participant, HonorDrive.Factory, r.NextDouble());
GenericEquation hd = AgentInitializer.InitializeDriveComponent(honor, GenericEquation.Factory, (Equation)TangentEquation);
var ins = Drive.GenerateTypicalInputs(honor);
ParameterChangeActionChunk pac = World.NewParameterChangeActionChunk();
pac.Add(Participant.ACS, "MCS_RER_SELECTION_MEASURE", .5);
hd.Input.AddRange(ins);
hd.Parameters.MAX_ACTIVATION = 5;
honor.Commit(hd);
honor.Parameters.DRIVE_GAIN = (gr == Groups.PRIVATE) ? .1 / 5 : .2 / 5;
Participant.Commit(honor);
ParameterSettingModule lpm = AgentInitializer.InitializeMetaCognitiveModule(Participant, ParameterSettingModule.Factory);
ACSLevelProbabilitySettingEquation lpe = AgentInitializer.InitializeMetaCognitiveDecisionNetwork(lpm, ACSLevelProbabilitySettingEquation.Factory, Participant);
lpe.Input.Add(honor.GetDriveStrength());
lpm.Commit(lpe);
Participant.Commit(lpm);
lpm.Parameters.FIXED_BL_LEVEL_SELECTION_MEASURE = 1;
lpm.Parameters.FIXED_RER_LEVEL_SELECTION_MEASURE = 0;
//Pre-train the IDN in the ACS
PreTrainACS(idn);
}
static void Main(string[] args)
{
//Initialize the task
Console.WriteLine("Initializing the Full Hello World Task");
int CorrectCounter = 0;
int NumberTrials = 20000;
Random rand = new Random();
World.LoggingLevel = TraceLevel.Off;
int progress = 0;
TextWriter orig = Console.Out;
StreamWriter sw = File.CreateText("HelloWorldFull.txt");
DimensionValuePair hi = World.NewDimensionValuePair("Salutation", "Hello");
DimensionValuePair bye = World.NewDimensionValuePair("Salutation", "Goodbye");
ExternalActionChunk sayHi = World.NewExternalActionChunk("Hello");
ExternalActionChunk sayBye = World.NewExternalActionChunk("Goodbye");
GoalChunk salute = World.NewGoalChunk("Salute");
GoalChunk bidFarewell = World.NewGoalChunk("Bid Farewell");
//Initialize the Agent
Agent John = World.NewAgent("John");
SimplifiedQBPNetwork net = AgentInitializer.InitializeImplicitDecisionNetwork(John, SimplifiedQBPNetwork.Factory);
net.Input.Add(salute, "goals");
net.Input.Add(bidFarewell, "goals");
net.Input.Add(hi);
net.Input.Add(bye);
net.Output.Add(sayHi);
net.Output.Add(sayBye);
net.Parameters.LEARNING_RATE = 1;
John.Commit(net);
John.ACS.Parameters.VARIABLE_BL_BETA = .5;
John.ACS.Parameters.VARIABLE_RER_BETA = .5;
John.ACS.Parameters.VARIABLE_IRL_BETA = 0;
John.ACS.Parameters.VARIABLE_FR_BETA = 0;
RefineableActionRule.GlobalParameters.SPECIALIZATION_THRESHOLD_1 = -.6;
RefineableActionRule.GlobalParameters.GENERALIZATION_THRESHOLD_1 = -.1;
RefineableActionRule.GlobalParameters.INFORMATION_GAIN_OPTION = RefineableActionRule.IGOptions.PERFECT;
AffiliationBelongingnessDrive ab = AgentInitializer.InitializeDrive(John, AffiliationBelongingnessDrive.Factory, rand.NextDouble(), (DeficitChangeProcessor)HelloWorldFull_DeficitChange);
DriveEquation abd = AgentInitializer.InitializeDriveComponent(ab, DriveEquation.Factory);
ab.Commit(abd);
John.Commit(ab);
AutonomyDrive aut = AgentInitializer.InitializeDrive(John, AutonomyDrive.Factory, rand.NextDouble(), (DeficitChangeProcessor)HelloWorldFull_DeficitChange);
DriveEquation autd =
AgentInitializer.InitializeDriveComponent(aut, DriveEquation.Factory);
aut.Commit(autd);
John.Commit(aut);
GoalSelectionModule gsm =
AgentInitializer.InitializeMetaCognitiveModule(John, GoalSelectionModule.Factory);
GoalSelectionEquation gse =
AgentInitializer.InitializeMetaCognitiveDecisionNetwork(gsm, GoalSelectionEquation.Factory);
gse.Input.Add(ab.GetDriveStrength());
gse.Input.Add(aut.GetDriveStrength());
GoalStructureUpdateActionChunk su = World.NewGoalStructureUpdateActionChunk();
GoalStructureUpdateActionChunk bu = World.NewGoalStructureUpdateActionChunk();
su.Add(GoalStructure.RecognizedActions.SET_RESET, salute);
bu.Add(GoalStructure.RecognizedActions.SET_RESET, bidFarewell);
gse.Output.Add(su);
gse.Output.Add(bu);
gsm.SetRelevance(su, ab, 1);
gsm.SetRelevance(bu, aut, 1);
gsm.Commit(gse);
John.Commit(gsm);
John.MS.Parameters.CURRENT_GOAL_ACTIVATION_OPTION =
MotivationalSubsystem.CurrentGoalActivationOptions.FULL;
//Run the task
Console.WriteLine("Running the Full Hello World Task");
Console.SetOut(sw);
SensoryInformation si;
ExternalActionChunk chosen;
for (int i = 0; i < NumberTrials; i++)
{
si = World.NewSensoryInformation(John);
si[AffiliationBelongingnessDrive.MetaInfoReservations.STIMULUS, typeof(AffiliationBelongingnessDrive).Name] = 1;
si[AutonomyDrive.MetaInfoReservations.STIMULUS, typeof(AutonomyDrive).Name] = 1;
//Randomly choose an input to perceive.
if (rand.NextDouble() < .5)
{
//Say "Hello"
si.Add(hi, John.Parameters.MAX_ACTIVATION);
si.Add(bye, John.Parameters.MIN_ACTIVATION);
}
else
{
//Say "Goodbye"
si.Add(hi, John.Parameters.MIN_ACTIVATION);
si.Add(bye, John.Parameters.MAX_ACTIVATION);
}
//Perceive the sensory information
John.Perceive(si);
//Choose an action
chosen = John.GetChosenExternalAction(si);
//Deliver appropriate feedback to the agent
if (chosen == sayHi)
{
//The agent said "Hello".
if (si[hi] == John.Parameters.MAX_ACTIVATION)
{
//The agent responded correctly
Trace.WriteLineIf(World.LoggingSwitch.TraceWarning, "John was correct");
//Record the agent's success.
CorrectCounter++;
//Give positive feedback.
John.ReceiveFeedback(si, 1.0);
}
else
{
//The agent responded incorrectly
Trace.WriteLineIf(World.LoggingSwitch.TraceWarning, "John was incorrect");
//Give negative feedback.
John.ReceiveFeedback(si, 0.0);
}
}
else
{
//The agent said "Goodbye".
if (si[bye] == John.Parameters.MAX_ACTIVATION)
{
//The agent responded correctly
Trace.WriteLineIf(World.LoggingSwitch.TraceWarning, "John was correct");
//Record the agent's success.
CorrectCounter++;
//Give positive feedback.
John.ReceiveFeedback(si, 1.0);
}
else
{
//The agent responded incorrectly
Trace.WriteLineIf(World.LoggingSwitch.TraceWarning, "John was incorrect");
//Give negative feedback.
John.ReceiveFeedback(si, 0.0);
}
}
Console.SetOut(orig);
progress = (int)(((double)(i + 1) / (double)NumberTrials) * 100);
Console.CursorLeft = 0;
Console.Write(progress + "% Complete..");
Console.SetOut(sw);
}
//Report Results
Console.WriteLine("Reporting Results for the Full Hello World Task");
Console.WriteLine("John got " + CorrectCounter + " correct out of " + NumberTrials + " trials (" +
(int)Math.Round(((double)CorrectCounter / (double)NumberTrials) * 100) + "%)");
Console.WriteLine("At the end of the task, John had learned the following rules:");
foreach (var i in John.GetInternals(Agent.InternalContainers.ACTION_RULES))
{
Console.WriteLine(i);
}
sw.Close();
Console.SetOut(orig);
Console.CursorLeft = 0;
Console.WriteLine("100% Complete..");
//Kill the agent to end the task
Console.WriteLine("Killing John to end the program");
John.Die();
Console.WriteLine("John is Dead");
Console.WriteLine("The Full Hello World Task has finished");
Console.WriteLine("The results have been saved to \"HelloWorldFull.txt\"");
Console.Write("Press any key to exit");
Console.ReadKey(true);
}
