{"id":"https://openalex.org/W103679982","doi":null,"title":"Learning partially observable action schemas","display_name":"Learning partially observable action schemas","publication_year":2006,"publication_date":"2006-07-16","ids":{"openalex":"https://openalex.org/W103679982","mag":"103679982"},"language":"en","primary_location":{"id":"mag:103679982","doi":null,"is_oa":false,"landing_page_url":"https://www.aaai.org/Papers/AAAI/2006/AAAI06-144.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306420577","display_name":"National Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"National Conference on Artificial Intelligence","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5009660759","display_name":"Dafna Shahaf","orcid":"https://orcid.org/0000-0003-3261-0818","observed_orcids":["https://orcid.org/0000-0003-3261-0818"]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dafna Shahaf","raw_affiliation_strings":["Computer Science Department, University of Illinois, Urbana-Champaign, Urbana, IL#TAB#"],"raw_orcid":"https://orcid.org/0000-0003-3261-0818","affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Illinois, Urbana-Champaign, Urbana, IL#TAB#","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109409885","display_name":"Eyal Amir","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eyal Amir","raw_affiliation_strings":["Computer Science Department, University of Illinois, Urbana-Champaign, Urbana, IL#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Illinois, Urbana-Champaign, Urbana, IL#TAB#","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":2.9796,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.91841267,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"913","last_page":"919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.7797999978065491,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.7797999978065491,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.10819999873638153,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.09440000355243683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/action-schemas","display_name":"action schemas","score":0.8090000152587891},{"id":"https://openalex.org/keywords/relational-learning","display_name":"relational learning","score":0.6069999933242798},{"id":"https://openalex.org/keywords/action-effects","display_name":"action effects","score":0.5},{"id":"https://openalex.org/keywords/preconditions","display_name":"preconditions","score":0.7799999713897705},{"id":"https://openalex.org/keywords/conditional-effects","display_name":"conditional effects","score":0.7020000219345093},{"id":"https://openalex.org/keywords/polynomial-time-learning","display_name":"polynomial-time learning","score":0.5429999828338623},{"id":"https://openalex.org/keywords/generalization","display_name":"generalization","score":0.5400000214576721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7242637276649475},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5991290211677551},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.597728967666626},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.5045970678329468},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4211258590221405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38790905475616455},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36575552821159363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1960294246673584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16544610261917114},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:103679982","doi":null,"is_oa":false,"landing_page_url":"https://www.aaai.org/Papers/AAAI/2006/AAAI06-144.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306420577","display_name":"National Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"National Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W166089536","https://openalex.org/W1279140112","https://openalex.org/W1494688554","https://openalex.org/W1515851193","https://openalex.org/W1515891729","https://openalex.org/W1552549180","https://openalex.org/W1896341954","https://openalex.org/W2121863487","https://openalex.org/W2126185296","https://openalex.org/W2157117634","https://openalex.org/W2160067530","https://openalex.org/W2165789488","https://openalex.org/W2396715201","https://openalex.org/W2484153108","https://openalex.org/W3020831056","https://openalex.org/W3112180085"],"related_works":["https://openalex.org/W7097753665","https://openalex.org/W7098742013","https://openalex.org/W7010964596","https://openalex.org/W2188228549","https://openalex.org/W3006131858","https://openalex.org/W7100306163","https://openalex.org/W7100750551","https://openalex.org/W1559358587","https://openalex.org/W2509648442","https://openalex.org/W2158917616"],"abstract_inverted_index":{"We":[0],"present":[1,35],"an":[2,21,26],"algorithm":[3,16,73,96,162],"that":[4,33,42,56,122,169],"derives":[5],"actions'":[6],"effects":[7,41,155],"and":[8,25,40,46,75,91,106,130,132,148,151,158,174],"preconditions":[9,39],"in":[10,100,156],"partially":[11],"observable,":[12],"relational":[13,23,124],"domains.":[14],"Our":[15,119,161],"has":[17],"two":[18],"unique":[19],"features:":[20],"expressive":[22],"language,":[24],"exact":[27],"tractable":[28],"computation.":[29],"An":[30],"action-schema":[31,83,117],"language":[32],"we":[34,53],"permits":[36,152],"learning":[37,129,135,153],"of":[38,80,88,103,165,177],"include":[43],"implicit":[44],"objects":[45,144],"unstated":[47],"relationships":[48],"between":[49,143],"objects.":[50],"For":[51],"example,":[52],"can":[54,170],"learn":[55],"replacing":[57],"a":[58,77,86,166],"blown":[59],"fuse":[60],"turns":[61],"on":[62,110],"all":[63,81],"the":[64,101,116,123],"lights":[65],"whose":[66],"switch":[67],"is":[68],"set":[69],"to":[70],"on.":[71],"The":[72],"maintains":[74],"outputs":[76],"relational-logical":[78],"representation":[79],"possible":[82],"models":[84],"after":[85],"sequence":[87],"executed":[89],"actions":[90],"partial":[92],"observations.":[93],"Importantly,":[94],"our":[95],"takes":[97,163],"polynomial":[98],"time":[99,104],"number":[102],"steps":[105],"predicates.":[107],"Time":[108],"dependence":[109],"other":[111],"domain":[112],"parameters":[113],"varies":[114],"with":[115],"language.":[118],"experiments":[120],"show":[121],"structure":[125,168],"speeds":[126],"up":[127],"both":[128],"generalization,":[131],"outperforms":[133],"propositional":[134],"methods.":[136],"It":[137],"also":[138],"allows":[139],"establishing":[140],"apriori-unknown":[141],"connections":[142],"(e.g.":[145],"light":[146],"bulbs":[147],"their":[149],"switches),":[150],"conditional":[154],"realistic":[157],"complex":[159],"situations.":[160],"advantage":[164],"DAG":[167],"be":[171],"updated":[172],"efficiently":[173],"preserves":[175],"compactness":[176],"representation.":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2016-06-24T00:00:00"}
