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IMPALA Scalable Distributed Deep RL With Importance Weighted Actor Learner Architectures
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Implementation of Scalable-Distributed-Deep-RL-with-Importance-Weighted-Actor-Learner-Architectures
These results are from only 4 threads. So unstable to train.
Tensorflow Implementation
A3C type thread environment training method
PongDeterministic-v4 environment
Todo
Only CPU Training method
Use Network protocol method
Training on GPU, Inference on CPU
Reference
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
deepmind/scalable_agent
Asynchronous_Advatnage_Actor_Critic
Open Source Agenda is not affiliated with "IMPALA Scalable Distributed Deep RL With Importance Weighted Actor Learner Architectures" Project. README Source:
RLOpensource/IMPALA-Scalable-Distributed-Deep-RL-with-Importance-Weighted-Actor-Learner-Architectures
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Last Commit
4 years ago
Tags
Deep Reinforcement Learning
Impala
Importance Sampling
Multi Threading
Reinforcement Learning
Tensorflow
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