{"id":"https://openalex.org/W4405033761","doi":"https://doi.org/10.48550/arxiv.2412.00985","title":"Provable Partially Observable Reinforcement Learning with Privileged Information","display_name":"Provable Partially Observable Reinforcement Learning with Privileged Information","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4405033761","doi":"https://doi.org/10.48550/arxiv.2412.00985"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2412.00985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00985","pdf_url":"https://arxiv.org/pdf/2412.00985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.00985","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115596012","display_name":"Yang Cai","orcid":"https://orcid.org/0009-0007-7379-3100"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087633300","display_name":"Xiangyu Liu","orcid":"https://orcid.org/0000-0003-3255-1467"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059265986","display_name":"Argyris Oikonomou","orcid":"https://orcid.org/0000-0002-6456-0109"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oikonomou, Argyris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047410441","display_name":"Kaiqing Zhang","orcid":"https://orcid.org/0000-0002-7446-7581"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Kaiqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8766000270843506,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8766000270843506,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14011","display_name":"Elevator Systems and Control","score":0.771399974822998,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.7361999750137329,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.804284930229187},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7770283222198486},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4769893288612366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46474120020866394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3670872449874878},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.32341474294662476},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16450750827789307},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1609811782836914},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.08182668685913086},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.08104303479194641}],"concepts":[{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.804284930229187},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7770283222198486},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4769893288612366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46474120020866394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3670872449874878},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.32341474294662476},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16450750827789307},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1609811782836914},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.08182668685913086},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.08104303479194641}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2412.00985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00985","pdf_url":"https://arxiv.org/pdf/2412.00985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.00985","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.00985","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2412.00985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00985","pdf_url":"https://arxiv.org/pdf/2412.00985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G386075326","display_name":"CAREER: Towards a Robust Theory of Mechanism Design","funder_award_id":"1942583","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4140470877","display_name":null,"funder_award_id":"CCF-1942583","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5259331294","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G5662081527","display_name":null,"funder_award_id":"CCF-2342642","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6946941417","display_name":"AF: Small: Equilibrium Computation and Multi-Agent Learning in High-Dimensional Games","funder_award_id":"2342642","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306151","display_name":"Alfred P. Sloan Foundation","ror":"https://ror.org/052csg198"},{"id":"https://openalex.org/F4320334164","display_name":"Simons Institute for the Theory of Computing, University of California Berkeley","ror":null},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405033761.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1994680671","https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2000283393","https://openalex.org/W2920061524","https://openalex.org/W2002320543","https://openalex.org/W2061947244","https://openalex.org/W2150232912","https://openalex.org/W1977959518","https://openalex.org/W2054940838"],"abstract_inverted_index":{"Partial":[0],"observability":[1],"of":[2,42,65,85,114,124,170,180],"the":[3,20,40,62,86,90,120,177],"underlying":[4],"states":[5,23,158],"generally":[6],"presents":[7],"significant":[8],"challenges":[9],"for":[10,155],"reinforcement":[11],"learning":[12,156],"(RL).":[13],"In":[14],"practice,":[15],"certain":[16],"\\emph{privileged":[17],"information},":[18],"e.g.,":[19],"access":[21],"to":[22],"from":[24],"simulators,":[25],"has":[26,32],"been":[27],"exploited":[28],"in":[29,55,76,145,197,207],"training":[30],"and":[31,47,51,100,117,141,203],"achieved":[33],"prominent":[34],"empirical":[35,63,112,198],"successes.":[36],"To":[37],"better":[38],"understand":[39],"benefits":[41],"privileged":[43,187],"information,":[44],"we":[45,59,108,174],"revisit":[46],"examine":[48],"several":[49],"simple":[50],"practically":[52,224],"used":[53],"paradigms":[54,209],"this":[56],"setting.":[57],"Specifically,":[58],"first":[60],"formalize":[61],"paradigm":[64,113],"\\emph{expert":[66],"distillation}":[67],"(also":[68],"known":[69],"as":[70],"\\emph{teacher-student}":[71],"learning),":[72],"demonstrating":[73],"its":[74],"pitfall":[75],"finding":[77],"near-optimal":[78],"policies.":[79],"We":[80,131,189],"then":[81],"identify":[82],"a":[83,133,151,164,194,213],"condition":[84],"partially":[87,126,181],"observable":[88,125,127,182],"environment,":[89],"\\emph{deterministic":[91],"filter":[92],"condition},":[93],"under":[94,163],"which":[95,146,167],"expert":[96],"distillation":[97],"achieves":[98],"sample":[99,140,202],"computational":[101,143,205],"complexities":[102,206],"that":[103,159],"are":[104],"\\emph{both}":[105],"polynomial.":[106],"Furthermore,":[107],"investigate":[109,176],"another":[110],"useful":[111],"\\emph{asymmetric":[115],"actor-critic},":[116],"focus":[118,220],"on":[119,222],"more":[121],"challenging":[122],"setting":[123],"Markov":[128],"decision":[129],"processes.":[130],"develop":[132,190],"belief-weighted":[134],"asymmetric":[135],"actor-critic":[136],"algorithm":[137],"with":[138,186,200,212],"polynomial":[139,201],"quasi-polynomial":[142],"complexities,":[144],"one":[147],"key":[148],"component":[149],"is":[150,221],"new":[152],"provable":[153,178],"oracle":[154],"belief":[157],"preserve":[160],"\\emph{filter":[161],"stability}":[162],"misspecified":[165],"model,":[166],"may":[168],"be":[169],"independent":[171],"interest.":[172],"Finally,":[173],"also":[175],"efficiency":[179],"multi-agent":[183],"RL":[184],"(MARL)":[185],"information.":[188],"algorithms":[191],"featuring":[192],"\\emph{centralized-training-with-decentralized-execution},":[193],"popular":[195],"framework":[196],"MARL,":[199],"(quasi-)polynomial":[204],"both":[208],"above.":[210],"Compared":[211],"few":[214],"recent":[215],"related":[216],"theoretical":[217],"studies,":[218],"our":[219],"understanding":[223],"inspired":[225],"algorithmic":[226],"paradigms,":[227],"without":[228],"computationally":[229],"intractable":[230],"oracles.":[231]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
