{"id":"https://openalex.org/W7203404","doi":null,"title":"A Survey of Model-Based and Model-Free Methods for Resolving Perceptual Aliasing","display_name":"A Survey of Model-Based and Model-Free Methods for Resolving Perceptual Aliasing","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W7203404","mag":"7203404"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.329.6691","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.6691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bgu.ac.il/~shanigu/papers/Survey.pdf","raw_type":"text"},"volume":null,"type":"article","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/A5006317361","display_name":"Guy Shani","orcid":"https://orcid.org/0000-0003-4131-0382","observed_orcids":["https://orcid.org/0000-0003-4131-0382","https://orcid.org/0000-0002-3655-7148"]},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Guy Shani","raw_affiliation_strings":["Ben Gurion University of the Negev"],"raw_orcid":"https://orcid.org/0000-0003-4131-0382","affiliations":[{"raw_affiliation_string":"Ben Gurion University of the Negev","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006317361"],"corresponding_institution_ids":["https://openalex.org/I124227911"],"apc_list":null,"apc_paid":null,"fwci":1.3026,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81652593,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"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":0.9990000128746033,"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":0.9990000128746033,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.0003000000142492354,"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/perceptual-aliasing","display_name":"perceptual aliasing","score":0.996999979019165},{"id":"https://openalex.org/keywords/model-based-reinforcement-learning","display_name":"model-based reinforcement learning","score":0.7950000166893005},{"id":"https://openalex.org/keywords/model-free-reinforcement-learning","display_name":"model-free reinforcement learning","score":0.9990000128746033},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-processes","display_name":"partially observable Markov decision processes","score":0.8970000147819519},{"id":"https://openalex.org/keywords/sensor-noise","display_name":"sensor noise","score":0.7300000190734863},{"id":"https://openalex.org/keywords/optimal-control","display_name":"optimal control","score":0.5210000276565552}],"concepts":[{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.8882884979248047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6919108033180237},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.6606168150901794},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.554258406162262},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5200628638267517},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49665457010269165},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49501699209213257},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4794991612434387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4667615592479706},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.43670016527175903},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.3505121171474457},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.23616233468055725},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17181900143623352},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.329.6691","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.329.6691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.bgu.ac.il/~shanigu/papers/Survey.pdf","raw_type":"text"},{"id":"mag:7203404","doi":null,"is_oa":false,"landing_page_url":"https://www.cs.bgu.ac.il/~shanigu/papers/Survey.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"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":63,"referenced_works":["https://openalex.org/W6242441","https://openalex.org/W11162148","https://openalex.org/W27992807","https://openalex.org/W32785352","https://openalex.org/W108082272","https://openalex.org/W131709709","https://openalex.org/W161873470","https://openalex.org/W183139520","https://openalex.org/W1483935885","https://openalex.org/W1484113995","https://openalex.org/W1486341833","https://openalex.org/W1486632395","https://openalex.org/W1494689917","https://openalex.org/W1499371387","https://openalex.org/W1517260920","https://openalex.org/W1539054658","https://openalex.org/W1539216098","https://openalex.org/W1540337045","https://openalex.org/W1553173248","https://openalex.org/W1555801537","https://openalex.org/W1557073320","https://openalex.org/W1583380718","https://openalex.org/W1594297126","https://openalex.org/W1595634327","https://openalex.org/W1640774615","https://openalex.org/W1657542410","https://openalex.org/W1657674574","https://openalex.org/W1687873425","https://openalex.org/W1701684472","https://openalex.org/W1801737117","https://openalex.org/W2009533501","https://openalex.org/W2028145673","https://openalex.org/W2048226872","https://openalex.org/W2052117683","https://openalex.org/W2057399676","https://openalex.org/W2064675550","https://openalex.org/W2096426448","https://openalex.org/W2107726111","https://openalex.org/W2108519123","https://openalex.org/W2110338773","https://openalex.org/W2113013121","https://openalex.org/W2113913482","https://openalex.org/W2121863487","https://openalex.org/W2123542217","https://openalex.org/W2144283793","https://openalex.org/W2148160361","https://openalex.org/W2149126181","https://openalex.org/W2150459019","https://openalex.org/W2153175335","https://openalex.org/W2154384352","https://openalex.org/W2158282517","https://openalex.org/W2158548602","https://openalex.org/W2158823144","https://openalex.org/W2159498728","https://openalex.org/W2160067530","https://openalex.org/W2164056559","https://openalex.org/W2166610875","https://openalex.org/W2166696997","https://openalex.org/W2168359464","https://openalex.org/W2334782222","https://openalex.org/W2341171179","https://openalex.org/W2763384692","https://openalex.org/W2912185451"],"related_works":["https://openalex.org/W7098815634","https://openalex.org/W7097589127","https://openalex.org/W1657674574","https://openalex.org/W2411359688","https://openalex.org/W1597746863","https://openalex.org/W1508784758","https://openalex.org/W1594297126","https://openalex.org/W3021189423","https://openalex.org/W3030709113","https://openalex.org/W7048177580"],"abstract_inverted_index":{"We":[0],"focus":[1],"our":[2],"attention":[3],"on":[4],"agents":[5,63],"learning":[6,58,96],"to":[7,55,73],"act":[8,56],"in":[9,45],"an":[10,105],"unknown":[11],"domain":[12],"using":[13,108],"noisy":[14],"sensors.":[15],"Such":[16],"domains":[17],"may":[18],"be":[19,31],"modeled":[20],"by":[21],"a":[22,59,97],"Partially":[23],"Observable":[24],"Markov":[25],"Decision":[26],"Process":[27],"(POMDP)":[28],"that":[29,53],"can":[30],"solved":[32],"optimally.":[33],"However,":[34,76],"when":[35],"the":[36,39,46,62,81,92,101,109],"model":[37,99],"of":[38,83,100],"environment":[40],"is":[41,91],"unknown,":[42],"most":[43],"research":[44],"area":[47],"studies":[48],"model-free":[49,69,119],"methods":[50,52,70,85],"\u2014":[51,95],"learn":[54],"without":[57],"model.":[60,111],"When":[61],"\u2019":[64],"sensors":[65],"provide":[66],"deterministic":[67],"output,":[68],"produce":[71],"close":[72],"optimal":[74,106],"results.":[75],"as":[77],"sensor":[78],"noise":[79],"increases,":[80],"accuracy":[82],"such":[84],"decreases.":[86],"Another,":[87],"less":[88],"explored,":[89],"option":[90],"model-based":[93,117],"approach":[94],"POMDP":[98],"world,":[102],"and":[103,118],"computing":[104],"solution":[107],"learned":[110],"In":[112],"this":[113],"survey":[114],"we":[115],"explore":[116],"techniques":[120],"for":[121],"handling":[122],"perceptual":[123],"aliasing.":[124],"2":[125]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2016-06-24T00:00:00"}