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arXiv · 2410.22524

Hindsight Experience Replay Accelerates Proximal Policy Optimization

Douglas C. Crowder·Darrien M. McKenzie·Matthew L. Trappett·Frances S. Chance
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Abstract

Hindsight experience replay (HER) accelerates off-policy reinforcement learning algorithms for environments that emit sparse rewards by modifying the goal of the episode post-hoc to be some state achieved during the episode. Because post-hoc modification of the observed goal violates the assumptions of on-policy algorithms, HER is not typically applied to on-policy algorithms. Here, we show that HER can dramatically accelerate proximal policy optimization (PPO), an on-policy reinforcement learning algorithm, when tested on a custom predator-prey environment.

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Douglas C. Crowder, Darrien M. McKenzie, Matthew L. Trappett, Frances S. Chance. 2024-10-29. Hindsight Experience Replay Accelerates Proximal Policy Optimization. https://arxiv.org/abs/2410.22524

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