// Use this for initialization void Start() { environment.isContinuou = false; QNetworkSimple network = new QNetworkSimple(2, 2, 2, 64, DeviceDescriptor.CPUDevice, 0.4f); model = new DQLModel(network); //QNetworkSimple networkTarget = new QNetworkSimple(2, 2, 2, 64, DeviceDescriptor.CPUDevice, 1f); //modelTarget = new DQLModel(networkTarget); //trainer = new TrainerDQLSimple(model, null, LearnerDefs.MomentumSGDLearner(startLearningRate,0.9f),1, experienceBufferSize, 500); trainer = new TrainerDQLSimple(model, modelTarget, LearnerDefs.AdamLearner(startLearningRate), 1, experienceBufferSize, 500); //Save();//test }
// Use this for initialization void Start() { QNetworkSimple network = new QNetworkSimple(6, 3, 2, 64, DeviceDescriptor.GPUDevice(0), 0.4f); model = new DQLModel(network); QNetworkSimple networkTarget = new QNetworkSimple(6, 3, 2, 64, DeviceDescriptor.GPUDevice(0), 0.4f); modelTarget = new DQLModel(networkTarget); //trainer = new TrainerDQLSimple(model, null, LearnerDefs.SGDLearner(startLearningRate),1, experienceBufferSize, 2048); trainer = new TrainerDQLSimple(model, modelTarget, LearnerDefs.AdamLearner(startLearningRate), 1, experienceBufferSize, experienceBufferSize); //Save();//test }
// Use this for initialization void Start() { //QNetworkSimple network = new QNetworkSimple(environment.mazeDimension.x* environment.mazeDimension.y, 4, 3, 64, DeviceDescriptor.CPUDevice, 0.4f); var network = new QNetworkConvSimple(environment.mazeDimension.x, environment.mazeDimension.y, 1, 4, new int[] { 3, 3 }, new int[] { 64, 128 }, new int[] { 1, 1 }, new bool[] { true, true }, 1, 128, false, DeviceDescriptor.GPUDevice(0), 1f); model = new DQLModel(network); //QNetworkSimple networkTarget = new QNetworkSimple(environment.mazeDimension.x * environment.mazeDimension.y, 4, 3, 64, DeviceDescriptor.CPUDevice, 0.4f); //modelTarget = new DQLModel(networkTarget); //trainer = new TrainerDQLSimple(model, modelTarget, LearnerDefs.SGDLearner(startLearningRate), 1, experienceBufferSize, 500); trainer = new TrainerDQLSimple(model, null, LearnerDefs.SGDLearner(startLearningRate), 1, experienceBufferSize, 500); //Save();//test }