Exemplo n.º 1
0
        //double MaxGhostDiff = 0.0000001;

        //List<double> PreviousOutput = new List<double>();

        public MMLocPacMemory(List <double> NNWeights, List <double> AStarWeights = null, int InputC = 0, int HiddenC = 0, int OutputC = 0, bool NearNodesOnly = false)
            : base("MMLocPacMemory")
        {
            InputCount  = InputC == 0 ? 24 : InputC;
            HiddenCount = HiddenC == 0 ? 1 : HiddenC;
            OutputCount = OutputC == 0 ? 12 : OutputC;

            this.NearNodesOnly = NearNodesOnly;

            Network = new ActivationNetwork(new BipolarSigmoidFunction(sigmoidAlphaValue), InputCount, HiddenCount, OutputCount);

            EvoWeights = new EvolutionWeights(Network);
            EvoWeights.SetWeights(NNWeights);
            //Network.UpdateVisibleWeights();

            if (AStarWeights != null)
            {
                this.AStarWeights = new List <int>();
                foreach (var W in AStarWeights)
                {
                    this.AStarWeights.Add((int)W);
                }
            }

            //for (int i = 0; i < OutputCount; i++) PreviousOutput.Add(0);
        }
Exemplo n.º 2
0
        //List<double> PreviousOutput = new List<double>();

        public MMPac(List <double> NNWeights)
            : base("MMPac")
        {
            Network = new ActivationNetwork(new BernoulliFunction(), InputCount, 5, 5, OutputCount);

            EvoWeights = new EvolutionWeights(Network);
            EvoWeights.SetWeights(NNWeights);
            //Network.UpdateVisibleWeights();

            //for (int i = 0; i < OutputCount; i++) PreviousOutput.Add(0);
        }
Exemplo n.º 3
0
        public MMLocPac(string LoadFromFile = "")
            : base("MMLocPac")
        {
            //TODO: change this to load from SaveLocPacToFile

            if (LoadFromFile.Length > 0)
            {
                EvoWeights = new EvolutionWeights(null);
                Network    = (ActivationNetwork)EvoWeights.LoadWeightsFromFile(LoadFromFile);
            }
            else
            {
                Network = new DeepBeliefNetwork(new BernoulliFunction(), InputCount, 10, OutputCount);
            }
        }
Exemplo n.º 4
0
        public MMPac(string LoadFromFile = "")
            : base("MMPac")
        {
            if (LoadFromFile.Length > 0)
            {
                EvoWeights = new EvolutionWeights(null);
                Network    = EvoWeights.LoadWeightsFromFile(LoadFromFile);
            }
            else
            {
                Network = new DeepBeliefNetwork(new BernoulliFunction(), InputCount, OutputCount);
            }

            //for (int i = 0; i < OutputCount; i++) PreviousOutput.Add(0);
        }
Exemplo n.º 5
0
        //List<double> PreviousOutput = new List<double>();

        public MMLocPac(List <double> NNWeights, List <int> AStarWeights = null)
            : base("MMLocPac")
        {
            Network = new ActivationNetwork(new BernoulliFunction(), InputCount, 10, OutputCount);

            EvoWeights = new EvolutionWeights(Network);
            EvoWeights.SetWeights(NNWeights);
            //Network.UpdateVisibleWeights();

            if (AStarWeights != null)
            {
                this.AStarWeights = AStarWeights;
            }

            //for (int i = 0; i < OutputCount; i++) PreviousOutput.Add(0);
        }
Exemplo n.º 6
0
        public MMLocPacMemory(string LoadFromFile = "")
            : base("MMLocPacMemory")
        {
            //TODO: change this to load from SaveLocPacToFile

            if (LoadFromFile.Length > 0)
            {
                EvoWeights = new EvolutionWeights(null);
                Network    = EvoWeights.LoadWeightsFromFile(LoadFromFile);

                InputCount = Network.InputsCount;
            }
            else
            {
                Network = new ActivationNetwork(new BipolarSigmoidFunction(sigmoidAlphaValue), InputCount, HiddenCount, OutputCount);
            }
        }