{"id":1372,"date":"2023-07-11T09:38:27","date_gmt":"2023-07-11T08:38:27","guid":{"rendered":"https:\/\/babel.isa.uma.es\/kipr\/?p=1372"},"modified":"2023-07-11T09:38:27","modified_gmt":"2023-07-11T08:38:27","slug":"building-pomdps-under-logical-constraints","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=1372","title":{"rendered":"Building POMDPs under logical constraints"},"content":{"rendered":"<h4>Bo Wu, Xiaobin Zhang, Hai Lin, <strong>Supervisor synthesis of POMDP via automata learning,<\/strong> . Automatica, Volume 129, 2021 <a href=\"https:\/\/doi.org\/10.1016\/j.automatica.2021.109654\" target=\"_blank\">DOI: 10.1016\/j.automatica.2021.109654<\/a>.<\/h4>\n<blockquote><p>Partially observable Markov decision process (POMDP) is a comprehensive modeling framework that captures uncertainties from sensing noises, actuation errors, and environments. Traditional POMDP planning finds an optimal policy for reward maximization. However, for safety-critical applications, it is often necessary to guarantee system performance described by high-level temporal logic specifications. Hence, we are motivated to develop a supervisor synthesis framework for POMDP with respect to given formal specifications. We propose an iterative learning-based algorithm, which can learn a permissive policy in the form of a deterministic finite automaton. A human\u2013robot collaboration case study validates the proposed algorithm.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Bo Wu, Xiaobin Zhang, Hai Lin, Supervisor synthesis of POMDP via automata learning, . Automatica, Volume 129, 2021 DOI: 10.1016\/j.automatica.2021.109654. <span class=\"ellipsis\">&hellip;<\/span> <span class=\"more-link-wrap\"><a href=\"https:\/\/babel.isa.uma.es\/kipr\/?p=1372\" class=\"more-link\"><span>Read More &rarr;<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[37],"tags":[466,116],"class_list":["post-1372","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","tag-constrained-task-planning","tag-pomdps"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1372"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1372"}],"version-history":[{"count":1,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1372\/revisions"}],"predecessor-version":[{"id":1373,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1372\/revisions\/1373"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1372"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1372"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1372"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}