Esempio n. 1
0
        public static void Begin()
        {
            //var parameters = new AdjustedTestableNetworkParameters
            //{
            //    Test = test,
            //    Network = NeuralArchitecture.CreateLayered(
            //        test.InputSize,
            //        test.OutputSize,
            //        () => new Synapse(),
            //        () => new ActivationNeuron(new LinearActivationFunction(1)),
            //        true,
            //        20, 10)
            //};

            var parameters = new AdjustedTestableNetworkParameters
            {
                Test = test,
                Network = NeuralArchitecture.CreateFullConnected(
                                test.InputSize,
                                test.OutputSize,
                                20,
                                () => new Synapse(),
                                () => new ActivationNeuron(new LinearActivationFunction(1)),
                                true)
            };

            var factory = new AdjustedNeuralNetworkBodyFactory(parameters);

            factory.CrossoverChunkSize = IntRange.CreateFixed((parameters.Network.ConnectionCount + parameters.Network.NodeCount) / 2 - 1);
            //factory.CrossoverChunkSize = new InclusiveRange(10, 10);

            factory.PointMutationChance = 0.005;

            var population = new AdjustedNeuralNetworkPopulation();
            population.ChanceOfMigration = 0.1;

            for (int idx = 0; idx < groupCount; idx++)
            {
                var group = new AdjustedNeuralNetworkGroup(
                    factory,
                    groupSize);
                //group.SelectionStrategy = new RandomSelectionStrategy();
                population.Groups.Add(group);
            }

            var context = new GAContext(population);
            context.BestBodyArrived += OnBestArrived;
            context.Start();
            Console.ReadKey();
            context.Stop();
        }
        private AdjustedNeuralNetworkPopulation DoCreate(NeuralNetwork network, NeuralNetworkTest test, out AdjustedNeuralNetworkBodyFactory bodyFactory)
        {
            var parameters = new AdjustedTestableNetworkParameters
            {
                Test = test,
                Network = network,
                MutationStrength = MutationStrength
            };

            bodyFactory = new AdjustedNeuralNetworkBodyFactory(parameters);

            if (CrossoverChunkSize.HasValue)
            {
                bodyFactory.CrossoverChunkSize = CrossoverChunkSize.Value;
            }
            else
            {
                bodyFactory.CrossoverChunkSize = IntRange.CreateFixed(parameters.AdjustableItems.Length / 2 - 1);
            }

            bodyFactory.PointMutationChance = PointMutationChance;

            var newPop = new AdjustedNeuralNetworkPopulation();
            newPop.ChanceOfMigration = ChanceOfMigration;

            for (int gIdx = 0; gIdx < groupCount; gIdx++)
            {
                var group = new AdjustedNeuralNetworkGroup(bodyFactory, groupSize);
                if (SelectionStrategy != null) group.SelectionStrategy = SelectionStrategy;
                newPop.Groups.Add(group);
            }

            return newPop;
        }