{"id":"https://openalex.org/W7161976426","doi":"https://doi.org/10.48550/arxiv.2605.21240","title":"APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents","display_name":"APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161976426","doi":"https://doi.org/10.48550/arxiv.2605.21240"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21240","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21240","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.2605.21240","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136712348","display_name":"Yibo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yibo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136711185","display_name":"Jiashuo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jiashuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136666561","display_name":"Zhi Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Zhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136639994","display_name":"Zhiyuan Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Zhiyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136634934","display_name":"Yuan Sui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sui, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136668182","display_name":"Shizun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shizun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123940415","display_name":"Yufei He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Yufei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136632863","display_name":"Bryan Hooi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hooi, Bryan","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/T11574","display_name":"Artificial Intelligence in Games","score":0.7519000172615051,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.7519000172615051,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.10849999636411667,"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":0.03610000014305115,"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/robustness","display_name":"Robustness (evolution)","score":0.5159000158309937},{"id":"https://openalex.org/keywords/autonomous-agent","display_name":"Autonomous agent","score":0.41749998927116394},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.3310999870300293},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.322299987077713},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.31929999589920044},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.3158000111579895}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.670799970626831},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5159000158309937},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35850000381469727},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34619998931884766},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.31929999589920044},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3066999912261963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2818000018596649},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21240","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21240","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.2605.21240","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21240","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":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7798931002616882}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLM":[0],"agents":[1,23,33,50],"have":[2],"shown":[3],"strong":[4],"performance":[5],"across":[6,41,149],"a":[7,91,131],"wide":[8],"range":[9],"of":[10,68,97],"complex":[11],"tasks,":[12],"including":[13],"interactive":[14],"environments":[15],"that":[16],"require":[17],"long-horizon":[18],"decision":[19],"making.":[20],"But":[21],"these":[22,49],"cannot":[24],"learn":[25],"on":[26,124],"the":[27,66,108],"fly":[28],"at":[29],"test":[30],"time.":[31],"Self-evolving":[32],"address":[34,73],"this":[35,74],"by":[36],"accumulating":[37],"memory":[38,57],"and":[39,84,119,129,146],"reflection":[40],"episodes":[42],"rather":[43],"than":[44],"requiring":[45],"model-weight":[46],"updates.":[47],"However,":[48],"often":[51],"suffer":[52],"from":[53],"exploration":[54,118,157],"collapse:":[55],"as":[56],"grows,":[58],"behavior":[59],"concentrates":[60],"around":[61],"familiar":[62],"high-reward":[63],"routines,":[64],"reducing":[65],"chance":[67],"discovering":[69],"better":[70],"alternatives.":[71],"To":[72],"problem,":[75],"we":[76],"propose":[77],"Autonomous":[78],"Policy":[79,115],"EXploration":[80],"(APEX),":[81],"which":[82],"builds":[83],"maintains":[85],"an":[86],"explicit":[87],"strategy":[88,92],"space":[89],"through":[90],"map-a":[93],"directed":[94],"acyclic":[95],"graph":[96],"milestones":[98],"with":[99,110],"prerequisite":[100],"dependency":[101],"edges.":[102],"In":[103],"APEX,":[104],"Fork":[105],"Discovery":[106],"expands":[107],"map":[109],"evidence-grounded":[111],"unexplored":[112],"directions,":[113],"while":[114],"Selection":[116],"balances":[117],"exploitation":[120],"during":[121],"planning.":[122],"Evaluated":[123],"nine":[125],"Jericho":[126],"text-adventure":[127],"games":[128],"WebArena,":[130],"realistic":[132],"web":[133],"interaction":[134],"benchmark,":[135],"APEX":[136],"outperforms":[137],"all":[138],"baselines.":[139],"Extensive":[140],"ablations":[141],"validate":[142],"each":[143],"component's":[144],"contribution":[145],"demonstrate":[147],"robustness":[148],"diverse":[150],"settings,":[151],"demonstrating":[152],"APEX's":[153],"effectiveness":[154],"for":[155],"sustained":[156],"in":[158],"self-evolving":[159],"agents.":[160]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}