ml-agents

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目录树: e9dd195d

作者	SHA1	备注	提交日期
GitHub	4ac79742	Refactor reward signals into separate class (#2144 ) * Create new class (RewardSignal) that represents a reward signal. * Add value heads for each reward signal in the PPO model. * Make summaries agnostic to the type of reward signals, and log weighted rewards per reward signal. * Move extrinsic and curiosity rewards into this new structure. * Allow defining multiple reward signals in YAML file. Add documentation for this new structure.	6 年前

作者

SHA1

备注

提交日期

GitHub

4ac79742

Refactor reward signals into separate class (#2144 )

* Create new class (RewardSignal) that represents a reward signal. 
* Add value heads for each reward signal in the PPO model.
* Make summaries agnostic to the type of reward signals, and log weighted rewards per reward signal. 
* Move extrinsic and curiosity rewards into this new structure.
* Allow defining multiple reward signals in YAML file. Add documentation for this new structure.

6 年前

1 次代码提交 (e9dd195d-dac3-47b3-8ad6-608657e1e6fb)