Exemple #1
0
        static public NetworkModel DecodeToNetworkModel(ConcurrentNetwork network)
        {
            ModelNeuronList masterNeuronList = new ModelNeuronList();

            // loop all neurons and build a table keyed on id.
            Hashtable neuronTable = new Hashtable(network.MasterNeuronList.Count);

            foreach (Neuron neuron in network.MasterNeuronList)
            {
                ModelNeuron modelNeuron = new ModelNeuron(neuron.NeuronType, neuron.Id, ActivationFunctionFactory.GetActivationFunction("NullFn"));
                neuronTable.Add(modelNeuron.Id, modelNeuron);
                masterNeuronList.Add(modelNeuron);
            }

            // Loop through all of the connections (within the neurons)
            // Now we have a neuron table keyed on id we can attach the connections
            // to their source and target neurons.
            foreach (Neuron neuron in network.MasterNeuronList)
            {
                foreach (Connection connection in neuron.ConnectionList)
                {
                    ModelConnection modelConnection = new ModelConnection();
                    modelConnection.Weight       = connection.Weight;
                    modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connection.SourceNeuronId];
                    modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connection.TargetNeuronId];

                    modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
                    modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
                }
            }

            return(new NetworkModel(masterNeuronList));
        }
Exemple #2
0
        static public NetworkModel DecodeToNetworkModel(NeatGenome.NeatGenome g)
        {
            ModelNeuronList masterNeuronList = new ModelNeuronList();

            // loop all neurons and build a table keyed on id.
            HybridDictionary neuronTable = new HybridDictionary(g.NeuronGeneList.Count);

            foreach (NeuronGene neuronGene in g.NeuronGeneList)
            {
                ModelNeuron modelNeuron = new ModelNeuron(neuronGene.NeuronType, neuronGene.InnovationId, neuronGene.ActivationFunction);
                neuronTable.Add(modelNeuron.Id, modelNeuron);
                masterNeuronList.Add(modelNeuron);
            }

            // Loop through all of the connections.
            // Now we have a neuron table keyed on id we can attach the connections
            // to their source and target neurons.
            foreach (ConnectionGene connectionGene in g.ConnectionGeneList)
            {
                ModelConnection modelConnection = new ModelConnection();
                modelConnection.Weight       = connectionGene.Weight;
                modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connectionGene.SourceNeuronId];
                modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connectionGene.TargetNeuronId];

                modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
                modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
            }

            return(new NetworkModel(masterNeuronList));
        }
		public NetworkModel(ModelNeuronList masterNeuronList)
		{
			bounds = new Size(0,0);
			
			this.masterNeuronList = masterNeuronList;
			foreach(ModelNeuron modelNeuron in masterNeuronList)
			{
				// Build the various lists.
				switch(modelNeuron.NeuronType)
				{
					case NeuronType.Bias:
					case NeuronType.Input:
						inputNeuronList.Add(modelNeuron);
						break;

					case NeuronType.Hidden:
						hiddenNeuronList.Add(modelNeuron);
						break;

					case NeuronType.Output:
						outputNeuronList.Add(modelNeuron);
						break;
				}
			}
		}
Exemple #4
0
        public NetworkModel(ModelNeuronList masterNeuronList)
        {
            bounds = new Size(0, 0);

            this.masterNeuronList = masterNeuronList;
            foreach (ModelNeuron modelNeuron in masterNeuronList)
            {
                // Build the various lists.
                switch (modelNeuron.NeuronType)
                {
                case NeuronType.Bias:
                case NeuronType.Input:
                    inputNeuronList.Add(modelNeuron);
                    break;

                case NeuronType.Hidden:
                    hiddenNeuronList.Add(modelNeuron);
                    break;

                case NeuronType.Output:
                    outputNeuronList.Add(modelNeuron);
                    break;
                }
            }
        }
		static public NetworkModel DecodeToNetworkModel(NeatGenome.NeatGenome g)
		{
			ModelNeuronList masterNeuronList = new ModelNeuronList();

			// loop all neurons and build a table keyed on id.
			HybridDictionary neuronTable = new HybridDictionary(g.NeuronGeneList.Count);
			foreach(NeuronGene neuronGene in g.NeuronGeneList)
			{
				ModelNeuron modelNeuron = new ModelNeuron(neuronGene.NeuronType, neuronGene.InnovationId,neuronGene.ActivationFunction);
				neuronTable.Add(modelNeuron.Id, modelNeuron);
				masterNeuronList.Add(modelNeuron);
			}

			// Loop through all of the connections.
			// Now we have a neuron table keyed on id we can attach the connections
			// to their source and target neurons.
			foreach(ConnectionGene connectionGene in g.ConnectionGeneList)
			{
				ModelConnection modelConnection = new ModelConnection();
				modelConnection.Weight = connectionGene.Weight;
				modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connectionGene.SourceNeuronId];
				modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connectionGene.TargetNeuronId];

				modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
				modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
			}

            //Sebastian. Build Model connections
            foreach (ModuleGene mg in g.ModuleGeneList)
            {
                foreach (uint sourceID in mg.InputIds)
                {
                    foreach (uint targetID in mg.OutputIds)
                    {
                        ModelConnection modelConnection = new ModelConnection();
                        modelConnection.Weight = 1.0; //TODO  connectionGene.Weight;
                        modelConnection.SourceNeuron = (ModelNeuron)neuronTable[sourceID];
                        modelConnection.TargetNeuron = (ModelNeuron)neuronTable[targetID];

                        modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
                        modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
                    }
                }
            }

			return new NetworkModel(masterNeuronList);
		}
		static public NetworkModel DecodeToNetworkModel(ConcurrentNetwork network)
		{
			ModelNeuronList masterNeuronList = new ModelNeuronList();
			
			// loop all neurons and build a table keyed on id.
			Hashtable neuronTable = new Hashtable(network.MasterNeuronList.Count);
			foreach(Neuron neuron in network.MasterNeuronList)
			{	
				ModelNeuron modelNeuron = new ModelNeuron(neuron.NeuronType, neuron.Id,ActivationFunctionFactory.GetActivationFunction("NullFn"));
				neuronTable.Add(modelNeuron.Id, modelNeuron);
				masterNeuronList.Add(modelNeuron);
			}

			// Loop through all of the connections (within the neurons)
			// Now we have a neuron table keyed on id we can attach the connections
			// to their source and target neurons.
			foreach(Neuron neuron in network.MasterNeuronList)
			{
				foreach(Connection connection in neuron.ConnectionList)
				{
					ModelConnection modelConnection = new ModelConnection();
					modelConnection.Weight = connection.Weight;
					modelConnection.SourceNeuron = (ModelNeuron)neuronTable[connection.SourceNeuronId];
					modelConnection.TargetNeuron = (ModelNeuron)neuronTable[connection.TargetNeuronId];

					modelConnection.SourceNeuron.OutConnectionList.Add(modelConnection);
					modelConnection.TargetNeuron.InConnectionList.Add(modelConnection);
				}
			}

			return new NetworkModel(masterNeuronList);
		}