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

目录树: 6ca50994

文件历史

GitHub 93760bc4 Adds SubprocessUnityEnvironment for parallel envs (#1751 ) This commit adds support for running Unity environments in parallel. An abstract base class was created for UnityEnvironment which a new SubprocessUnityEnvironment inherits from. SubprocessUnityEnvironment communicates through a pipe in order to send commands which will be run in parallel to its workers. A few significant changes needed to be made as a side-effect: * UnityEnvironments are created via a factory method (a closure) rather than being directly created by the main process. * In mlagents-learn "worker-id" has been replaced by "base-port" and "num-envs", and worker_ids are automatically assigned across runs. * BrainInfo objects now convert all fields to numpy arrays or lists to avoid serialization issues.	6 年前
..
test_subprocess_unity_environment.py	Adds SubprocessUnityEnvironment for parallel envs (#1751)	6 年前

GitHub 93760bc4 Adds SubprocessUnityEnvironment for parallel envs (#1751 )

This commit adds support for running Unity environments in parallel.
An abstract base class was created for UnityEnvironment which a new
SubprocessUnityEnvironment inherits from.

SubprocessUnityEnvironment communicates through a pipe in order to
send commands which will be run in parallel to its workers.

A few significant changes needed to be made as a side-effect:
* UnityEnvironments are created via a factory method (a closure)
  rather than being directly created by the main process.
* In mlagents-learn "worker-id" has been replaced by "base-port"
  and "num-envs", and worker_ids are automatically assigned across runs.
* BrainInfo objects now convert all fields to numpy arrays or lists to
  avoid serialization issues.

6 年前

test_subprocess_unity_environment.py

Adds SubprocessUnityEnvironment for parallel envs (#1751)

6 年前