ml-agents

Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目，它使游戏和模拟能够作为训练智能代理的环境。

unity3d unity unity-tech reinforcement-le deep-learning deep-reinforcement-learning neural-networks

文件历史

GitHub 2d68b835 Check that worker port is available in RpcCommunicator (#1415 ) * Check that worker port is available in RpcCommunicator Previously the RpcCommunicator did not check the port or create the RPC server until `initialize()` was called. Since "initialize" requires the environment to be available, this means we might create a new environment which connects to an existing RPC server running in another process. This causes both training runs to fail. As a remedy to this issue, this commit moves the server creation into the RpcCommunicator constructor and adds an explicit socket binding check to the requested port. * Fixes suggested by Codacy * Update rpc_communicator.py * Addressing feedback: formatting & consistency		6 年前
..
communicator_objects	Brains as Scriptable Objects (#1250)	6 年前
__init__.py	formating and added documentation	7 年前
brain.py	Add file check & reuse protobuf conversion functions (#1316)	6 年前
communicator.py	removed the logging.basicConfig in other files, so that we have one place to control this (#1285)	6 年前
environment.py	Add file check & reuse protobuf conversion functions (#1316)	6 年前
exception.py	Check that worker port is available in RpcCommunicator (#1415)	6 年前
rpc_communicator.py	Check that worker port is available in RpcCommunicator (#1415)	6 年前
socket_communicator.py	removed the logging.basicConfig in other files, so that we have one place to control this (#1285)	6 年前
utilities.py	Add file check & reuse protobuf conversion functions (#1316)	6 年前