Difference between revisions of "Distributed Deep Reinforcement Learning (DDRL)"
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[http://www.google.com/search?q=Distributed+Deep+Reinforcement+Learning+DeepRL+machine+learning+ML+artificial+intelligence ...Google search] | [http://www.google.com/search?q=Distributed+Deep+Reinforcement+Learning+DeepRL+machine+learning+ML+artificial+intelligence ...Google search] | ||
| + | * [[IMPALA (Importance Weighted Actor-Learner Architecture)]] | ||
| + | * [http://deepmind.com/blog/impala-scalable-distributed-deeprl-dmlab-30/ Importance Weighted Actor-Learner Architectures: Scalable Distributed DeepRL in DMLab-30] | ||
* [[Deep Reinforcement Learning (DRL)]] | * [[Deep Reinforcement Learning (DRL)]] | ||
| − | |||
| − | Deep Reinforcement Learning | + | a new, highly scalable agent architecture for distributed training called Importance Weighted Actor-Learner Architecture that uses a new off-policy correction algorithm called V-trace. |
| + | |||
| + | <youtube>YMfJLFynmA</youtube> | ||
| + | |||
| + | == DMLab-30 == | ||
| + | |||
| + | [http://www.youtube.com/results?search_query=DMLab-30+Distributed+Deep+Reinforcement+Learning+DeepRL Youtube search...] | ||
| + | [http://www.google.com/search?q=Distributed+DMLab-30+Deep+Reinforcement+Learning+DeepRL+machine+learning+ML+artificial+intelligence ...Google search] | ||
| + | |||
| + | DMLab-30 is a collection of new levels designed using our open source RL environment DeepMind Lab. These environments enable any DeepRL researcher to test systems on a large spectrum of interesting tasks either individually or in a multi-task setting. | ||
| − | + | * [http://github.com/deepmind/lab/tree/master/game_scripts/levels/contributed/dmlab30 DMLab-30 | GitHub] | |
Revision as of 21:35, 15 February 2019
Youtube search... ...Google search
- IMPALA (Importance Weighted Actor-Learner Architecture)
- Importance Weighted Actor-Learner Architectures: Scalable Distributed DeepRL in DMLab-30
- Deep Reinforcement Learning (DRL)
a new, highly scalable agent architecture for distributed training called Importance Weighted Actor-Learner Architecture that uses a new off-policy correction algorithm called V-trace.
DMLab-30
Youtube search... ...Google search
DMLab-30 is a collection of new levels designed using our open source RL environment DeepMind Lab. These environments enable any DeepRL researcher to test systems on a large spectrum of interesting tasks either individually or in a multi-task setting.
