A Succinct Summary of Reinforcement Learning
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Abstract (arXiv)
This document is a concise summary of many key results in single-agent reinforcement learning (RL). The intended audience are those who already have some familiarity with RL and are looking to review, reference and/or remind themselves of important ideas in the field.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 24 references that are in the map. First posted on arXiv 3 Jan 2023.
Builds on
4 of 24 references.
References · 4
- 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
- 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 1,653
- 2019Mastering Atari, Go, Chess and Shogi by Planning with a Learned Modelcited by 1,353
- 2015Prioritized Experience Replaycited by 1,099
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