static void SetupBPNetwork(Agent reasoner)
{
//Chunks for the whales, tuna, and bears
DeclarativeChunk TunaChunk = World.NewDeclarativeChunk("Tuna");
DeclarativeChunk WhaleChunk = World.NewDeclarativeChunk("Whale");
DeclarativeChunk BearChunk = World.NewDeclarativeChunk("Bear");
//The 2 properties (as DV pairs)
DimensionValuePair livesinwater = World.NewDimensionValuePair("lives in", "water");
DimensionValuePair eatsfish = World.NewDimensionValuePair("eats", "fish");
//The BP network to be used in the bottom level of the NACS
BPNetwork net = AgentInitializer.InitializeAssociativeMemoryNetwork(reasoner, BPNetwork.Factory);
//Adds the properties (as inputs) and chunks (as outputs) to the BP network
net.Input.Add(livesinwater);
net.Input.Add(eatsfish);
net.Output.Add(TunaChunk);
net.Output.Add(WhaleChunk);
net.Output.Add(BearChunk);
reasoner.Commit(net);
//Adds the chunks to the GKS
reasoner.AddKnowledge(TunaChunk);
reasoner.AddKnowledge(WhaleChunk);
reasoner.AddKnowledge(BearChunk);
//Initializes a trainer to use to train the BP network
GenericEquation trainer = ImplicitComponentInitializer.InitializeTrainer(GenericEquation.Factory, (Equation)trainerEQ);
//Adds the properties (as inputs) and chunks (as outputs) to the trainer
trainer.Input.Add(livesinwater);
trainer.Input.Add(eatsfish);
trainer.Output.Add(TunaChunk);
trainer.Output.Add(WhaleChunk);
trainer.Output.Add(BearChunk);
trainer.Commit();
//Sets up data sets for each of the 2 properties
List <ActivationCollection> sis = new List <ActivationCollection>();
ActivationCollection si = ImplicitComponentInitializer.NewDataSet();
si.Add(livesinwater, 1);
sis.Add(si);
si = ImplicitComponentInitializer.NewDataSet();
si.Add(eatsfish, 1);
sis.Add(si);
Console.Write("Training AMN...");
//Trains the BP network to report associative knowledge between the properties and the chunks
ImplicitComponentInitializer.Train(net, trainer, sis, ImplicitComponentInitializer.TrainingTerminationConditions.SUM_SQ_ERROR);
Console.WriteLine("Finished!");
}
public static void Main()
{
Console.WriteLine("Demonstrating Inductive Reasoning: Diversity Effect");
InitializeWorld();
//agent for reasoning
Agent reasoner = World.NewAgent();
//Adds all of the declarative chunks to the GKS
foreach (DeclarativeChunk dc in chunks)
{
reasoner.AddKnowledge(dc);
}
//Specifies that the NACS should perform 1 reasoning iterations
reasoner.NACS.Parameters.REASONING_ITERATION_COUNT = 1;
//Sets the conclusion threshold to .05
reasoner.NACS.Parameters.CONCLUSION_THRESHOLD = 0.05;
//Indicates that any chunks used as input should not be returned as part of the conclusion
reasoner.NACS.Parameters.RETURN_INPUTS_AS_CONCLUSIONS = false;
//Initiates reasoning and outputs the results
DoReasoning(reasoner);
//Kills the reasoning agent
reasoner.Die();
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
public static void Main()
{
Console.WriteLine("Demonstrating Inductive Reasoning: Typicality Effect");
InitializeWorld();
Agent reasoner = World.NewAgent();
//Adds all of the declarative chunks to the GKS
foreach (DeclarativeChunk dc in chunks)
{
reasoner.AddKnowledge(dc);
}
//Specifies that the NACS should perform 1 reasoning iterations
reasoner.NACS.Parameters.REASONING_ITERATION_COUNT = 1;
//Sets the conclusion threshold to .1
reasoner.NACS.Parameters.CONCLUSION_THRESHOLD = .1;
//Initiates reasoning and outputs the results
DoReasoning(reasoner);
//Kills the reasoning agent
reasoner.Die();
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
public static void Main()
{
Agent reasoner = World.NewAgent();
InitializeWorld(reasoner);
//Adds all of the declarative chunks to the GKS
foreach (DeclarativeChunk dc in chunks)
{
reasoner.AddKnowledge(dc);
}
//Initializes the Hopfield network in the bottom level of the NACS
HopfieldNetwork net = AgentInitializer.InitializeAssociativeMemoryNetwork
(reasoner, HopfieldNetwork.Factory);
//Species all of the dimension-value pairs as nodes for the Hopfield network
net.Nodes.AddRange(dvs);
//Commits the Hopfield network
reasoner.Commit(net);
//Encodes the patterns into the Hopfield network
EncodeHopfieldNetwork(net);
//Sets up the rules in the top level of the NAS
SetupRules(reasoner);
//Specifies that the NACS should perform 2 reasoning iterations
reasoner.NACS.Parameters.REASONING_ITERATION_COUNT = 2;
//Sets the conclusion threshold to 1
//(indicating that only fully matched conclusions should be returned)
reasoner.NACS.Parameters.CONCLUSION_THRESHOLD = 1;
//Initiates reasoning and outputs the results
DoReasoning(reasoner);
//Kills the reasoning agent
reasoner.Die();
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
public static void Main()
{
Agent reasoner = World.NewAgent();
InitializeWorld(reasoner);
//Adds all of the declarative chunks to the GKS
foreach (DeclarativeChunk dc in chunks)
{
reasoner.AddKnowledge(dc);
}
//Initializes the Hopfield network in the bottom level of the NACS
HopfieldNetwork net = AgentInitializer.InitializeAssociativeMemoryNetwork
(reasoner, HopfieldNetwork.Factory);
//Species all of the dimension-value pairs as nodes for the Hopfield network
net.Nodes.AddRange(dvs);
//Commits the Hopfield network
reasoner.Commit(net);
//Encodes the patterns into the Hopfield network
EncodeHopfieldNetwork(net);
//Specifies that the NACS should perform 2 reasoning iterations
reasoner.NACS.Parameters.REASONING_ITERATION_COUNT = 1;
//Sets the conclusion threshold to 1
//(indicating that only fully matched conclusions should be returned)
reasoner.NACS.Parameters.CONCLUSION_THRESHOLD = 1;
// Add Some Action Chunks for the ACS
World.NewExternalActionChunk("Yes");
World.NewExternalActionChunk("No");
ReasoningRequestActionChunk think = World.NewReasoningRequestActionChunk("DoReasoning");
think.Add(NonActionCenteredSubsystem.RecognizedReasoningActions.NEW, 1, false);
World.NewDimensionValuePair("state", 1);
World.NewDimensionValuePair("state", 2);
World.NewDimensionValuePair("state", 3);
// Add ACS Rule to use chunks
RefineableActionRule yes = AgentInitializer.InitializeActionRule(reasoner, RefineableActionRule.Factory, World.GetActionChunk("Yes"));
yes.GeneralizedCondition.Add(World.GetDeclarativeChunk(1), true);
reasoner.Commit(yes);
RefineableActionRule no = AgentInitializer.InitializeActionRule(reasoner, RefineableActionRule.Factory, World.GetActionChunk("No"));
no.GeneralizedCondition.Add(World.GetDeclarativeChunk(0), true, "altdim");
no.GeneralizedCondition.Add(World.GetDeclarativeChunk(2), true, "altdim");
no.GeneralizedCondition.Add(World.GetDeclarativeChunk(3), true, "altdim");
no.GeneralizedCondition.Add(World.GetDeclarativeChunk(4), true, "altdim");
reasoner.Commit(no);
RefineableActionRule doReasoning = AgentInitializer.InitializeActionRule(reasoner, RefineableActionRule.Factory, World.GetActionChunk("DoReasoning"));
doReasoning.GeneralizedCondition.Add(World.GetDimensionValuePair("state", 1));
reasoner.Commit(doReasoning);
RefineableActionRule doNothing = AgentInitializer.InitializeActionRule(reasoner, RefineableActionRule.Factory, ExternalActionChunk.DO_NOTHING);
doNothing.GeneralizedCondition.Add(World.GetDimensionValuePair("state", 2));
reasoner.Commit(doNothing);
reasoner.ACS.Parameters.PERFORM_RER_REFINEMENT = false;
reasoner.ACS.Parameters.FIXED_BL_LEVEL_SELECTION_MEASURE = 0;
reasoner.ACS.Parameters.FIXED_RER_LEVEL_SELECTION_MEASURE = 1;
reasoner.ACS.Parameters.FIXED_IRL_LEVEL_SELECTION_MEASURE = 0;
reasoner.ACS.Parameters.FIXED_FR_LEVEL_SELECTION_MEASURE = 0;
reasoner.ACS.Parameters.LEVEL_SELECTION_METHOD = ActionCenteredSubsystem.LevelSelectionMethods.STOCHASTIC;
reasoner.ACS.Parameters.LEVEL_SELECTION_OPTION = ActionCenteredSubsystem.LevelSelectionOptions.FIXED;
reasoner.ACS.Parameters.NACS_REASONING_ACTION_PROBABILITY = 1;
reasoner.ACS.Parameters.EXTERNAL_ACTION_PROBABILITY = 1;
reasoner.NACS.Parameters.REASONING_ITERATION_TIME = 3000;
//Initiates the simulation and outputs the results
Run(reasoner);
//Kills the reasoning agent
reasoner.Die();
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
