{"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/learning-to-share-and-hide-intentions-using","title":"Learning to Share and Hide Intentions using Information Regularization","arxiv_id":"1808.02093","date":"2018-08-06","proceeding":"NeurIPS 2018 12","authors":["DJ Strouse","Max Kleiman-Weiner","Josh Tenenbaum","Matt Botvinick","David Schwab"],"abstract":"Learning to cooperate with friends and compete with foes is a key component\nof multi-agent reinforcement learning. Typically to do so, one requires access\nto either a model of or interaction with the other agent(s). Here we show how\nto learn effective strategies for cooperation and competition in an asymmetric\ninformation game with no such model or interaction. Our approach is to\nencourage an agent to reveal or hide their intentions using an\ninformation-theoretic regularizer. We consider both the mutual information\nbetween goal and action given state, as well as the mutual information between\ngoal and state. We show how to optimize these regularizers in a way that is\neasy to integrate with policy gradient reinforcement learning. Finally, we\ndemonstrate that cooperative (competitive) policies learned with our approach\nlead to more (less) reward for a second agent in two simple asymmetric\ninformation games.","url_abs":"http://arxiv.org/abs/1808.02093v2","url_pdf":"http://arxiv.org/pdf/1808.02093v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"learning-to-share-and-hide-intentions-using","repo_url":"https://github.com/djstrouse/InfoMARL","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"multi-agent-reinforcement-learning","task_name":"Multi-agent Reinforcement Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.02093","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}