Hao_hu Generalisable Episodic Memory for Drl 2021
[TOC] Title: Generalisable episodic memory for Deep Reinforcement Learning Author: Hao Hu et. al. Publish Year: Jun 2021 Review Date: April 2022 Summary of paper Motivation The author proposed Generalisable Episodic Memory (GEM), which effectively organises the state-action values of episodic memory in a generalisable manner and supports implicit planning on memorised trajectories. so compared to traditional memory table, GEM learns a virtual memory table memorized by deep neural networks to aggregate similar state-action pairs that essentially have the same nature....