{"id":"https://openalex.org/W2159136633","doi":"https://doi.org/10.5555/2627435.2750354","title":"Efficient learning and planning with compressed predictive states","display_name":"Efficient learning and planning with compressed predictive states","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2159136633","doi":"https://doi.org/10.5555/2627435.2750354","mag":"2159136633"},"language":"en","primary_location":{"id":"mag:2159136633","is_oa":false,"landing_page_url":"http://jmlr.org/papers/volume15/hamilton14a/hamilton14a.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null},"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004542284","display_name":"William L. Hamilton","orcid":"https://orcid.org/0000-0002-3330-353X"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"William L. Hamilton","raw_affiliation_strings":["School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017397456","display_name":"Mahdi Milani Fard","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mahdi Milani Fard","raw_affiliation_strings":["School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080591144","display_name":"Jo\u00eblle Pineau","orcid":"https://orcid.org/0000-0003-0747-7250"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jo\u00eblle Pineau","raw_affiliation_strings":["School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#"],"raw_orcid":"https://orcid.org/0000-0003-0747-7250","affiliations":[{"raw_affiliation_string":"School of Computer Science, McGill University, Montr\u00e9al, QC Canada#TAB#","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5023651"],"apc_list":null,"apc_paid":null,"fwci":4.1418,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.94460959,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"15","issue":"1","first_page":"3395","last_page":"3439"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9991000294685364,"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":0.9991000294685364,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9919999837875366,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7143948078155518},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.555691659450531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5392332077026367},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.48129263520240784},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4785535931587219},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.46663743257522583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4578927457332611},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4260643422603607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7143948078155518},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.555691659450531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5392332077026367},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.48129263520240784},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4785535931587219},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.46663743257522583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4578927457332611},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4260643422603607},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2159136633","is_oa":false,"landing_page_url":"http://jmlr.org/papers/volume15/hamilton14a/hamilton14a.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Journal of Machine Learning Research","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W15793533","https://openalex.org/W69985676","https://openalex.org/W87961591","https://openalex.org/W203249681","https://openalex.org/W1506832649","https://openalex.org/W1515851193","https://openalex.org/W1528086278","https://openalex.org/W1540337045","https://openalex.org/W1543510660","https://openalex.org/W1560153690","https://openalex.org/W1565405003","https://openalex.org/W1573412864","https://openalex.org/W1583380718","https://openalex.org/W1604021599","https://openalex.org/W1700863064","https://openalex.org/W1726002263","https://openalex.org/W1861901279","https://openalex.org/W1986736933","https://openalex.org/W2042830238","https://openalex.org/W2053171205","https://openalex.org/W2056132907","https://openalex.org/W2070996757","https://openalex.org/W2102949476","https://openalex.org/W2109910161","https://openalex.org/W2110121428","https://openalex.org/W2112490010","https://openalex.org/W2115571765","https://openalex.org/W2120346334","https://openalex.org/W2120710106","https://openalex.org/W2121863487","https://openalex.org/W2137509429","https://openalex.org/W2149960632","https://openalex.org/W2154384352","https://openalex.org/W2157544132","https://openalex.org/W2158282517","https://openalex.org/W2161581368","https://openalex.org/W2164013269","https://openalex.org/W2166610875","https://openalex.org/W2168359464","https://openalex.org/W2171084228","https://openalex.org/W2208906386","https://openalex.org/W2258438951","https://openalex.org/W2296250998","https://openalex.org/W2569025259","https://openalex.org/W2569188995","https://openalex.org/W2952772488","https://openalex.org/W2962790067","https://openalex.org/W3038099828"],"related_works":["https://openalex.org/W2569188995","https://openalex.org/W2158282517","https://openalex.org/W2950653703","https://openalex.org/W2168359464","https://openalex.org/W2154384352","https://openalex.org/W2042830238","https://openalex.org/W1540337045","https://openalex.org/W2171084228","https://openalex.org/W2524962924","https://openalex.org/W1528086278","https://openalex.org/W2166610875","https://openalex.org/W2215498041","https://openalex.org/W2198300770","https://openalex.org/W2163126463","https://openalex.org/W2146746928","https://openalex.org/W1532688806","https://openalex.org/W2208906386","https://openalex.org/W69985676","https://openalex.org/W2123542217","https://openalex.org/W164910094"],"abstract_inverted_index":{"Predictive":[0],"state":[1,48],"representations":[2],"(PSRs)":[3],"offer":[4,54],"an":[5,51,55],"expressive":[6],"framework":[7,57,162],"for":[8,58,137],"modelling":[9],"partially":[10,181],"observable":[11,20,182],"systems.":[12],"By":[13],"compactly":[14],"representing":[15],"systems":[16],"as":[17,50],"functions":[18],"of":[19,77,94,108,141,193],"quantities,":[21],"the":[22,75,92,106,145,190],"PSR":[23],"learning":[24,61,114,138,150],"approach":[25,115,132,173],"avoids":[26],"using":[27],"local-minima":[28],"prone":[29],"expectation-maximization":[30],"and":[31,84,125,176],"instead":[32],"employs":[33],"a":[34,45,67,71,88,134,160,184],"globally":[35],"optimal":[36],"moment-based":[37],"algorithm.":[38],"Moreover,":[39],"since":[40],"PSRs":[41,78,95,110],"do":[42],"not":[43],"require":[44],"predetermined":[46],"latent":[47],"structure":[49],"input,":[52],"they":[53],"attractive":[56],"model-based":[59],"reinforcement":[60],"when":[62],"agents":[63],"must":[64],"plan":[65],"without":[66,189],"priori":[68],"access":[69],"to":[70,100],"system":[72],"model.":[73],"Unfortunately,":[74],"expressiveness":[76],"comes":[79],"with":[80,149],"significant":[81],"computational":[82,146],"cost,":[83],"this":[85,102,131,172],"cost":[86],"is":[87,187],"major":[89],"factor":[90],"inhibiting":[91],"use":[93,192],"in":[96,119,178],"applications.":[97],"In":[98],"order":[99],"alleviate":[101],"shortcoming,":[103],"we":[104,158,169],"introduce":[105],"notion":[107],"compressed":[109,126],"(CPSRs).":[111],"The":[112],"CPSR":[113],"combines":[116],"recent":[117],"advancements":[118],"dimensionality":[120],"reduction,":[121],"incremental":[122],"matrix":[123],"decomposition,":[124],"sensing.":[127],"We":[128],"show":[129,170],"how":[130],"provides":[133],"principled":[135,191],"avenue":[136],"accurate":[139],"approximations":[140],"PSRs,":[142],"drastically":[143],"reducing":[144],"costs":[147],"associated":[148],"while":[151],"also":[152],"providing":[153],"effective":[154],"regularization.":[155],"Going":[156],"further,":[157],"propose":[159],"planning":[161,177],"which":[163],"exploits":[164],"these":[165],"learned":[166],"models.":[167],"And":[168],"that":[171,186],"facilitates":[174],"model-learning":[175],"large":[179],"complex":[180],"domains,":[183],"task":[185],"infeasible":[188],"compression.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1}],"updated_date":"2025-10-10T17:16:08.811792","created_date":"2025-10-10T00:00:00"}