{"id":"https://openalex.org/W7163881306","doi":"https://doi.org/10.48550/arxiv.2606.07127","title":"Learning Explicit Behavioral Models with Adaptive Questions and World-Model Probes","display_name":"Learning Explicit Behavioral Models with Adaptive Questions and World-Model Probes","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163881306","doi":"https://doi.org/10.48550/arxiv.2606.07127"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.07127","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07127","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.07127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063339544","display_name":"Hikaru Shindo","orcid":"https://orcid.org/0000-0001-7129-6118"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shindo, Hikaru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138140985","display_name":"Yu Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135952558","display_name":"Teng Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Teng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059077091","display_name":"Quentin Delfosse","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Delfosse, Quentin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010748686","display_name":"Christopher Tauchmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tauchmann, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036345046","display_name":"Jannis Bl\u00fcml","orcid":"https://orcid.org/0000-0002-9400-0946"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bl\u00fcml, Jannis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011721474","display_name":"Gopika Sudhakaran","orcid":"https://orcid.org/0009-0007-3721-5602"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sudhakaran, Gopika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138156888","display_name":"Kristian Kersting","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kersting, Kristian","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":false,"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":0.6840000152587891,"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":0.6840000152587891,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.11339999735355377,"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":0.050599999725818634,"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/executable","display_name":"Executable","score":0.789900004863739},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6917999982833862},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5968000292778015},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5532000064849854},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.492000013589859},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.44279998540878296},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.38600000739097595},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.3763999938964844}],"concepts":[{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.789900004863739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7188000082969666},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6917999982833862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255999803543091},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5532000064849854},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.492000013589859},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.44279998540878296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4410000145435333},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.34869998693466187},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C68784500","wikidata":"https://www.wikidata.org/wiki/Q1570691","display_name":"Adaptive behavior","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.2685000002384186},{"id":"https://openalex.org/C83804111","wikidata":"https://www.wikidata.org/wiki/Q1063558","display_name":"Behavioral pattern","level":2,"score":0.26429998874664307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.07127","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07127","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.07127","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.07127","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.40212664008140564}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Interactive":[0],"agents":[1],"trained":[2],"only":[3,56],"against":[4],"task":[5,73,146],"return":[6],"can":[7,42,174],"achieve":[8],"high":[9],"scores":[10],"while":[11,162],"failing":[12],"to":[13,27],"represent":[14],"the":[15,97,154],"mechanisms":[16],"that":[17,71,143,171],"make":[18],"their":[19],"actions":[20],"succeed.":[21],"This":[22],"makes":[23],"brittle":[24],"behavior":[25,44,86],"difficult":[26],"diagnose":[28],"and":[29,39,50,79,94,106,117,126,149,166,180],"limits":[30],"adaptation":[31],"when":[32],"environment":[33],"dynamics":[34],"change.":[35],"Existing":[36],"LLM":[37],"reflection":[38],"policy-code":[40],"repair":[41],"revise":[43],"from":[45],"failed":[46],"trajectories,":[47],"but":[48],"questions":[49,116,173],"world-understanding":[51],"tests":[52],"are":[53,137],"usually":[54],"used":[55],"after":[57],"training.":[58],"We":[59],"introduce":[60],"an":[61],"Explicit":[62],"Symbolic":[63],"Behavioral":[64],"Model":[65],"(ESBM),":[66],"a":[67,140],"trainable":[68],"behavioral":[69],"model":[70],"couples":[72],"performance":[74],"with":[75],"evidence-grounded":[76],"question":[77],"answering":[78],"executable":[80,167],"mechanism":[81,95,98,168],"prediction.":[82],"An":[83],"ESBM":[84,133,158],"represents":[85],"through":[87],"typed":[88],"predicates,":[89],"weighted":[90],"rules,":[91],"bounded":[92],"options":[93],"memory;":[96],"layer":[99],"predicts":[100],"symbolic":[101],"events,":[102],"object":[103],"changes,":[104],"rewards":[105],"terminal":[107],"consequences":[108],"under":[109],"action":[110],"interventions.":[111],"After":[112],"each":[113],"rollout,":[114],"adaptive":[115,172],"active":[118,150],"world-model":[119,151],"probes":[120],"convert":[121],"score":[122],"failures,":[123],"QA":[124],"errors":[125,128],"transition-prediction":[127],"into":[129],"constraints":[130],"for":[131,183],"local":[132],"edits.":[134],"Candidate":[135],"models":[136],"selected":[138],"by":[139],"multi-criterion":[141],"rule":[142],"jointly":[144],"evaluates":[145],"score,":[147],"answerability":[148],"consistency.":[152],"Under":[153],"tested":[155],"Atari-style":[156],"protocols,":[157],"learns":[159],"high-scoring":[160],"policies":[161],"producing":[163],"explicit":[164],"answers":[165],"predictions,":[169],"indicating":[170],"serve":[175],"as":[176],"both":[177],"training":[178],"pressure":[179],"reusable":[181],"benchmarks":[182],"mechanistic":[184],"policy":[185],"learning":[186],"in":[187],"this":[188],"setting.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-09T00:00:00"}