{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/causal-influence-detection-for-improving","title":"Causal Influence Detection for Improving Efficiency in Reinforcement Learning","arxiv_id":"2106.03443","date":"2021-06-07","proceeding":"NeurIPS 2021 12","authors":["Maximilian Seitzer","Bernhard Schölkopf","Georg Martius"],"abstract":"Many reinforcement learning (RL) environments consist of independent entities that interact sparsely. In such environments, RL agents have only limited influence over other entities in any particular situation. 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