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codes for the paper "POMO: Policy Optimization with Multiple Optima for Reinforcement Learning"

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POMO

Files in "OLD_ipynb_ver" folders

They are the original codes (2020) used for the paper

POMO: Policy Optimization with Multiple Optima for Reinforcement Learning
accepted at NeurIPS 2020
http://arxiv.org/abs/2010.16011 https://proceedings.neurips.cc/paper/2020/hash/f231f2107df69eab0a3862d50018a9b2-Abstract.html

They are based on ipynb files and easier to play with interactively.


Files in "NEW_py_ver" folders

They are the updated codes, newly structured in 2021.
They are based on py files, so that they can be run on servers more easily.

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codes for the paper "POMO: Policy Optimization with Multiple Optima for Reinforcement Learning"

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  • Python 76.2%
  • Jupyter Notebook 23.8%