BY571 / IQN-and-Extensions

PyTorch Implementation of Implicit Quantile Networks (IQN) for Distributional Reinforcement Learning with additional extensions like PER, Noisy layer, N-step bootstrapping, Dueling architecture and parallel env support.

Date Created 2020-08-12 (4 years ago)

Commits 37 (last one 4 years ago)

Stargazers 81 (0 this week)

Watchers 4 (0 this week)

Forks 16

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RepositoryStats indexes 595,856 repositories, of these BY571/IQN-and-Extensions is ranked #339,331 (43rd percentile) for total stargazers, and #377,401 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #8,468/17,543.

BY571/IQN-and-Extensions is also tagged with popular topics, for these it's ranked: pytorch (#3,945/6025), reinforcement-learning (#820/1337), parallel-computing (#140/210)

Other Information

BY571/IQN-and-Extensions has 1 open pull request on Github, 1 pull request has been merged over the lifetime of the repository.

Github issues are enabled, there are 2 open issues and 4 closed issues.

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dqn iqn pytorch rainbow munchausen noisy-layer distributional-r multi-environment parallel-computing parallel-processing n-step-bootstrapping pytorch-implementation reinforcement-learning implicit-quantile-networks prioritized-experience-replay reinforcement-learning-algorithms

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updated: 2024-11-13 @ 11:48am, id: 287046687 / R_kgDOERv8Hw