// 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
}
