{"id":"https://openalex.org/W4403488054","doi":"https://doi.org/10.3233/faia240635","title":"Detecting Hidden Triggers: Mapping Non-Markov Reward Functions to Markov","display_name":"Detecting Hidden Triggers: Mapping Non-Markov Reward Functions to Markov","publication_year":2024,"publication_date":"2024-10-16","ids":{"openalex":"https://openalex.org/W4403488054","doi":"https://doi.org/10.3233/faia240635"},"language":"en","primary_location":{"id":"doi:10.3233/faia240635","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240635","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240635","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240635","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087959219","display_name":"Gregory Hyde","orcid":"https://orcid.org/0000-0001-5608-5224"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gregory Hyde","raw_affiliation_strings":["Thayer School of Engineering at Dartmouth College, Hanover, NH, USA"],"raw_orcid":"https://orcid.org/0000-0001-5608-5224","affiliations":[{"raw_affiliation_string":"Thayer School of Engineering at Dartmouth College, Hanover, NH, USA","institution_ids":["https://openalex.org/I107672454"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054636708","display_name":"Eugene Santos","orcid":"https://orcid.org/0000-0003-2923-5113"},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Santos, Jr.","raw_affiliation_strings":["Thayer School of Engineering at Dartmouth College, Hanover, NH, USA"],"raw_orcid":"https://orcid.org/0000-0003-2923-5113","affiliations":[{"raw_affiliation_string":"Thayer School of Engineering at Dartmouth College, Hanover, NH, USA","institution_ids":["https://openalex.org/I107672454"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I107672454"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37266709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.14270000159740448,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.14270000159740448,"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/markov-chain","display_name":"Markov chain","score":0.685263454914093},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5649652481079102},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5475900173187256},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5028738379478455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3606645464897156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2605138123035431}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.685263454914093},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5649652481079102},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5475900173187256},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5028738379478455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3606645464897156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2605138123035431}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia240635","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240635","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240635","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia240635","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia240635","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240635","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4403488054.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2084326697","https://openalex.org/W2194396582","https://openalex.org/W2027903142","https://openalex.org/W2082284720","https://openalex.org/W2116722627","https://openalex.org/W2537260108","https://openalex.org/W2354322608","https://openalex.org/W2158700654"],"abstract_inverted_index":{"Many":[0],"Reinforcement":[1],"Learning":[2],"algorithms":[3],"assume":[4],"a":[5,22,52,119,151],"Markov":[6,31],"reward":[7,15,27,36,92,124,135,148],"function":[8],"to":[9,60,90],"guarantee":[10],"optimality.":[11],"However,":[12],"not":[13,50],"all":[14],"functions":[16,28,136],"are":[17],"Markov.":[18],"This":[19],"paper":[20],"proposes":[21],"framework":[23],"for":[24,122],"mapping":[25,103],"non-Markov":[26,134],"into":[29],"equivalent":[30],"ones":[32],"by":[33,131],"learning":[34,45,78,100,132,147],"specialized":[35],"automata,":[37],"Reward":[38,46,79],"Machines.":[39],"Unlike":[40],"the":[41,75,138,144],"general":[42],"practice":[43],"of":[44,54,77,146],"Machines,":[47],"we":[48,63,142],"do":[49],"require":[51],"set":[53],"high-level":[55],"propositional":[56],"symbols":[57],"from":[58,68],"which":[59],"learn.":[61],"Rather,":[62],"learn":[64],"hidden":[65],"triggers,":[66],"directly":[67],"data,":[69],"that":[70,115],"construct":[71],"them.":[72],"We":[73,94,113,126],"demonstrate":[74,143],"importance":[76],"Machines":[80],"over":[81],"their":[82,88],"Deterministic":[83],"Finite-State":[84],"Automata":[85],"counterparts":[86],"given":[87],"ability":[89],"model":[91],"dependencies.":[93],"formalize":[95],"this":[96],"distinction":[97],"in":[98,137,150],"our":[99,116,129],"objective.":[101],"Our":[102],"process":[104],"is":[105],"constructed":[106],"as":[107],"an":[108],"Integer":[109],"Linear":[110],"Programming":[111],"problem.":[112],"prove":[114],"mappings":[117],"form":[118],"suitable":[120],"proxy":[121],"maximizing":[123],"expectations.":[125],"empirically":[127],"validate":[128],"approach":[130],"black-box,":[133],"Officeworld":[139],"domain.":[140],"Additionally,":[141],"effectiveness":[145],"dependencies":[149],"new":[152],"domain,":[153],"Breakfastworld.":[154]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
