International Conference on Computer and Knowledge Engineering

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Adaptive Prioritization in Experience Replay Using Feedback from Multiple Learning Signals

Authors :

Seyed Hossein Mostafavi¹ Mohammad Bagher Naghibi Sistani²

1- Ferdowsi university of mashhad 2- Ferdowsi university of mashhad

Keywords :

Deep reinforcement learning،experience replay،prioritized experience replay،multi-criteria sampling،adaptive weighting

Abstract :

Deep reinforcement learning (DRL) has made significant progress in recent years. Many DRL algorithms utilize experience replay to store past experiences and reuse them during training. One main challenge in this process is choosing which experiences to sample. While most previous methods rely on one or two sampling criteria, this study introduces a method that incorporates four distinct criteria, with their weights adaptively tuned based on environmental feedback. Simulation results demonstrate that the proposed method outperforms previous approaches in various reinforcement learning environments.

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