DQN-using-PyTorch和ML-Agents：如何使用PyTorch和ML-Agents环境实现基于矢量的DQN的简单...
需积分: 48 61 浏览量
2021-02-06
06:31:30
上传
评论 4
收藏 2.72MB ZIP 举报
DQN-using-PyTorch-and-ML-Agents-master.zip （65个子文件） 
DQN-using-PyTorch-and-ML-Agents-master 
dqnAgent_Trained_Model.pth 87KB test.py 6KB train.py 10KB media 
bananacollection.gif 2.39MB
exampleTrainingScoresGraph.jpg 22KB python learn.py 4KB trainer_config.yaml 4KB tests test_ppo.py 13KB test_unityagents.py 6KB test_unitytrainers.py 7KB mock_communicator.py 3KB __init__.py 54B test_bc.py 4KB unityagents curriculum.py 4KB __init__.py 99B socket_communicator.py 4KB communicator.py 1KB exception.py 2KB environment.py 24KB rpc_communicator.py 4KB brain.py 3KB Basics.ipynb 6KB
requirements.txt 160B setup.py 874B unitytrainers bc models.py 3KB __init__.py 45B trainer.py 15KB models.py 17KB trainer_controller.py 15KB __init__.py 182B trainer.py 7KB ppo models.py 13KB __init__.py 45B trainer.py 29KB buffer.py 11KB curricula push.json 555B test.json 275B wall.json 320B README.md 273B communicator_objects unity_rl_initialization_output_pb2.py 5KB header_pb2.py 3KB agent_info_proto_pb2.py 6KB engine_configuration_proto_pb2.py 4KB environment_parameters_proto_pb2.py 5KB space_type_proto_pb2.py 2KB unity_message_pb2.py 4KB agent_action_proto_pb2.py 3KB unity_rl_input_pb2.py 8KB __init__.py 720B resolution_proto_pb2.py 3KB unity_rl_output_pb2.py 7KB unity_output_pb2.py 4KB brain_parameters_proto_pb2.py 7KB unity_to_external_pb2_grpc.py 2KB command_proto_pb2.py 2KB brain_type_proto_pb2.py 2KB unity_to_external_pb2.py 2KB unity_input_pb2.py 4KB unity_rl_initialization_input_pb2.py 2KB LICENSE 34KB
Report.pdf 229KB model.py 1KB dqn_agent.py 7KB README.md 6KB replay_memory.py 3KB
评论0