Based on PARL, the PPO algorithm of deep reinforcement learning has been reproduced, reaching the same level of indicators as the paper in Atari benchmarks.
Include following approach:
Paper: PPO in Proximal Policy Optimization Algorithms
Please see here to know more about Mujoco games.
# To train an agent for HalfCheetah-v2 game (default: CLIP loss)
python train.py
# To train for different game and different loss type
# python train.py --env [ENV_NAME] --loss_type [CLIP|KLPEN]
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