{"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/planning-in-entropy-regularized-markov","title":"Planning in entropy-regularized Markov decision processes and games","arxiv_id":null,"date":"2019-12-01","proceeding":"NeurIPS 2019 12","authors":["Jean-bastien Grill","Omar Darwiche Domingues","Pierre Menard","Remi Munos","Michal Valko"],"abstract":"We propose SmoothCruiser, a new planning algorithm for estimating the value function in entropy-regularized Markov decision processes and two-player games, given a generative model of the SmoothCruiser. SmoothCruiser makes use of the smoothness of the Bellman operator promoted by the regularization to achieve problem-independent sample complexity of order $\\tilde{\\mathcal{O}}(1/\\epsilon^4)$ for a desired accuracy $\\epsilon$, whereas for non-regularized settings there are no known algorithms with guaranteed polynomial sample complexity in the worst case.","url_abs":"http://papers.nips.cc/paper/9405-planning-in-entropy-regularized-markov-decision-processes-and-games","url_pdf":"http://papers.nips.cc/paper/9405-planning-in-entropy-regularized-markov-decision-processes-and-games.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":"planning-in-entropy-regularized-markov","repo_url":"https://github.com/omardrwch/smoothcruiser-check","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}