{"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/memory-augmented-self-play","title":"Memory Augmented Self-Play","arxiv_id":"1805.11016","date":"2018-05-28","proceeding":null,"authors":["Shagun Sodhani","Vardaan Pahuja"],"abstract":"Self-play is an unsupervised training procedure which enables the\nreinforcement learning agents to explore the environment without requiring any\nexternal rewards. We augment the self-play setting by providing an external\nmemory where the agent can store experience from the previous tasks. This\nenables the agent to come up with more diverse self-play tasks resulting in\nfaster exploration of the environment. The agent pretrained in the memory\naugmented self-play setting easily outperforms the agent pretrained in\nno-memory self-play setting.","url_abs":"http://arxiv.org/abs/1805.11016v2","url_pdf":"http://arxiv.org/pdf/1805.11016v2.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":"memory-augmented-self-play","repo_url":"https://github.com/shagunsodhani/memory-augmented-self-play","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"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":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}