{"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/multi-agent-actor-critic-for-mixed","title":"Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments","arxiv_id":"1706.02275","date":"2017-06-07","proceeding":"NeurIPS 2017 12","authors":["Ryan Lowe","Yi Wu","Aviv Tamar","Jean Harb","Pieter Abbeel","Igor Mordatch"],"abstract":"We explore deep reinforcement learning methods for multi-agent domains. 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