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Code for Policy Consolidation for Continual Reinforcement Learning
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Code for Policy Consolidation for Continual Reinforcement Learning Accepted at ICML 2019 arXiv link: https://arxiv.org/abs/1902.00255 Python version used: anaconda3-5.1.0 Requirements: numpy, tensorflow 1.7.0, gym, baselines, gym_extensions, robosumo, gym-compete - tc.py contains the main classes and functions for the PC model - run_single.py and run_selfplay.py are the run files used for training agents in single agent and selfplay environments respectively - play_history.py is the run file for playing a self-play agent against its history or against other agents