{"id":"https://openalex.org/W4415428017","doi":"https://doi.org/10.3233/faia251256","title":"Generative Agents for Multi-Agent Autoformalization of Interaction Scenarios","display_name":"Generative Agents for Multi-Agent Autoformalization of Interaction Scenarios","publication_year":2025,"publication_date":"2025-10-21","ids":{"openalex":"https://openalex.org/W4415428017","doi":"https://doi.org/10.3233/faia251256"},"language":null,"primary_location":{"id":"doi:10.3233/faia251256","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251256","pdf_url":null,"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://doi.org/10.3233/faia251256","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025112559","display_name":"Agnieszka Mensfelt","orcid":"https://orcid.org/0000-0002-2385-2017"},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Agnieszka Mensfelt","raw_affiliation_strings":["Royal Holloway, University of London, Egham, Surrey, UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway, University of London, Egham, Surrey, UK","institution_ids":["https://openalex.org/I184558857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035046930","display_name":"Kostas Stathis","orcid":"https://orcid.org/0000-0002-9946-4037"},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kostas Stathis","raw_affiliation_strings":["Royal Holloway, University of London, Egham, Surrey, UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway, University of London, Egham, Surrey, UK","institution_ids":["https://openalex.org/I184558857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107421530","display_name":"Vince Trencsenyi","orcid":null},"institutions":[{"id":"https://openalex.org/I184558857","display_name":"Royal Holloway University of London","ror":"https://ror.org/04g2vpn86","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I184558857"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vince Trencsenyi","raw_affiliation_strings":["Royal Holloway, University of London, Egham, Surrey, UK"],"affiliations":[{"raw_affiliation_string":"Royal Holloway, University of London, Egham, Surrey, UK","institution_ids":["https://openalex.org/I184558857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025112559"],"corresponding_institution_ids":["https://openalex.org/I184558857"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.7193046,"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/T10703","display_name":"Business Process Modeling and Analysis","score":0.9523000121116638,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9523000121116638,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.9117000102996826,"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/correctness","display_name":"Correctness","score":0.8981999754905701},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.8068000078201294},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.585099995136261},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.5777999758720398},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5412999987602234},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3734999895095825},{"id":"https://openalex.org/keywords/natural","display_name":"Natural (archaeology)","score":0.35989999771118164},{"id":"https://openalex.org/keywords/semantic-data-model","display_name":"Semantic data model","score":0.3504999876022339}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.8981999754905701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8241000175476074},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.8068000078201294},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.585099995136261},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.5777999758720398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5515000224113464},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5321000218391418},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.4927999973297119},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3734999895095825},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.32580000162124634},{"id":"https://openalex.org/C37926939","wikidata":"https://www.wikidata.org/wiki/Q7449061","display_name":"Semantic equivalence","level":4,"score":0.2858999967575073},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25540000200271606},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia251256","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251256","pdf_url":null,"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/faia251256","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia251256","pdf_url":null,"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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-agent":[0],"simulations":[1,43],"are":[2,111],"a":[3,85],"versatile":[4],"tool":[5],"for":[6,30],"exploring":[7],"interactions":[8],"among":[9],"natural":[10,60,117],"and":[11,21,69,100,131,139,142],"artificial":[12],"agents,":[13],"but":[14],"their":[15],"development":[16],"typically":[17],"demands":[18],"domain":[19],"expertise":[20],"manual":[22],"effort.":[23],"This":[24],"work":[25],"introduces":[26],"the":[27,37,54,97],"Generative":[28],"Agents":[29],"Multi-Agent":[31],"Autoformalization":[32],"(GAMA)":[33],"framework,":[34],"which":[35],"automates":[36],"formalization":[38],"of":[39,56,63],"interaction":[40],"scenarios":[41,65],"in":[42,155],"using":[44],"agents":[45],"augmented":[46],"with":[47,80,115,135,146],"large":[48],"language":[49,61,118],"models":[50],"(LLMs).":[51],"To":[52,88],"demonstrate":[53],"application":[55],"GAMA,":[57],"we":[58,70],"use":[59],"descriptions":[62,119],"game-theoretic":[64],"representing":[66],"social":[67],"interactions,":[68],"autoformalize":[71],"them":[72],"into":[73],"executable":[74],"logic":[75],"programs":[76],"defining":[77],"game":[78],"rules,":[79],"syntactic":[81,130,141],"correctness":[82,134,145],"enforced":[83],"through":[84],"solver-based":[86],"validation.":[87],"ensure":[89],"runtime":[90],"validity,":[91],"an":[92],"iterative,":[93],"tournament-based":[94],"procedure":[95],"tests":[96],"generated":[98],"rules":[99],"strategies,":[101],"followed":[102],"by":[103],"exact":[104],"semantic":[105,133,144,153],"validation":[106],"when":[107],"ground":[108],"truth":[109],"outcomes":[110],"available.":[112],"In":[113],"experiments":[114],"110":[116],"across":[120],"five":[121],"2":[122,124],"\u00d7":[123],"simultaneous-move":[125],"games,":[126],"GAMA":[127],"achieves":[128],"100%":[129],"76.5%":[132],"Claude":[136],"3.5":[137],"Sonnet,":[138],"99.82%":[140],"77%":[143],"GPT-4o.":[147],"The":[148],"framework":[149],"also":[150],"shows":[151],"high":[152],"accuracy":[154],"autoformalizing":[156],"agents\u2019":[157],"strategies.":[158]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-24T00:00:00"}