{"id":"https://openalex.org/W7167890008","doi":"https://doi.org/10.48550/arxiv.2607.08233","title":"Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction","display_name":"Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction","publication_year":2026,"publication_date":"2026-07-09","ids":{"openalex":"https://openalex.org/W7167890008","doi":"https://doi.org/10.48550/arxiv.2607.08233"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.08233","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.08233","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2607.08233","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108320710","display_name":"Sophia Koehler","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koehler, Sophia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093931961","display_name":"Antonia W\u00fcst","orcid":"https://orcid.org/0009-0005-8636-1337"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"W\u00fcst, Antonia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005689692","display_name":"Inga Ibs","orcid":"https://orcid.org/0000-0001-5525-4356"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ibs, Inga","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125011931","display_name":"Wasu Top Piriyakulkij","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piriyakulkij, Wasu Top","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034737333","display_name":"Wolfgang Stammer","orcid":"https://orcid.org/0000-0003-3793-8046"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stammer, Wolfgang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133826742","display_name":"Constantin Rothkopf","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rothkopf, Constantin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140384958","display_name":"Kevin Ellis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ellis, Kevin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140429226","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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.24009999632835388,"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":0.24009999632835388,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.10040000081062317,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.08649999648332596,"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/perception","display_name":"Perception","score":0.532800018787384},{"id":"https://openalex.org/keywords/intelligent-agent","display_name":"Intelligent agent","score":0.48739999532699585},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4187999963760376},{"id":"https://openalex.org/keywords/autonomous-agent","display_name":"Autonomous agent","score":0.4002000093460083},{"id":"https://openalex.org/keywords/embodied-agent","display_name":"Embodied agent","score":0.3212999999523163},{"id":"https://openalex.org/keywords/rule-induction","display_name":"Rule induction","score":0.31060001254081726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6880999803543091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5450000166893005},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.532800018787384},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.48739999532699585},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4821999967098236},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4187999963760376},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38659998774528503},{"id":"https://openalex.org/C103683099","wikidata":"https://www.wikidata.org/wiki/Q5370102","display_name":"Embodied agent","level":3,"score":0.3212999999523163},{"id":"https://openalex.org/C2776780472","wikidata":"https://www.wikidata.org/wiki/Q7378945","display_name":"Rule induction","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.2757999897003174},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2678000032901764},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26330000162124634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.08233","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.08233","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2607.08233","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.08233","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"central":[1],"challenge":[2],"in":[3,38,91,144,169],"building":[4],"intelligent":[5,160],"systems":[6],"is":[7],"enabling":[8],"agents":[9,40,70,119,161],"to":[10,24,124],"jointly":[11],"perceive":[12],"complex":[13,150],"inputs,":[14],"form":[15],"hypotheses":[16,59],"about":[17,46],"hidden":[18],"patterns,":[19],"and":[20,56,81,107,116,162],"design":[21],"informative":[22],"experiments":[23],"test":[25],"them.":[26],"To":[27,129],"study":[28],"this":[29],"problem,":[30],"we":[31,133],"propose":[32,120],"ZendoWorld,":[33],"a":[34,43,142],"controlled":[35],"interactive":[36],"environment":[37],"which":[39,140],"must":[41],"infer":[42],"logical":[44],"rule":[45],"visual":[47],"game":[48,65],"observations,":[49],"acquire":[50],"information":[51],"by":[52],"proposing":[53],"new":[54],"scenes,":[55],"refine":[57],"their":[58],"based":[60],"on":[61,137],"feedback":[62],"from":[63],"the":[64,102,138],"environment.":[66],"We":[67],"evaluate":[68],"several":[69],"spanning":[71],"pure":[72],"VLM":[73],"reasoning,":[74,146],"Bayesian":[75],"particle":[76],"filtering,":[77],"dynamic":[78],"concept":[79],"discovery,":[80],"neuro-symbolic":[82],"methods.":[83],"Our":[84],"main":[85],"findings":[86],"are:":[87],"(1)":[88],"high":[89],"accuracy":[90],"predicting":[92],"labels":[93],"for":[94,112,148,166],"observed":[95],"examples":[96],"does":[97],"not":[98],"imply":[99],"recovery":[100],"of":[101],"underlying":[103],"rule;":[104],"(2)":[105],"perception":[106],"induction":[108],"are":[109],"distinct":[110],"bottlenecks":[111],"different":[113],"agent":[114],"classes;":[115],"(3)":[117],"VLM-based":[118],"near-uninformative":[121],"experiments,":[122],"failing":[123],"actively":[125],"reduce":[126],"hypothesis":[127],"uncertainty.":[128],"compare":[130],"these":[131],"results,":[132],"collect":[134],"human":[135],"data":[136],"task,":[139],"reveals":[141],"gap":[143],"inductive":[145],"particularly":[147,168],"more":[149],"rules.":[151],"Overall,":[152],"ZENDOWORLD":[153],"takes":[154],"an":[155],"important":[156],"step":[157],"toward":[158],"evaluating":[159],"identifies":[163],"concrete":[164],"avenues":[165],"improvement,":[167],"domains":[170],"like":[171],"scientific":[172],"discovery.":[173]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-11T00:00:00"}