{"id":"https://openalex.org/W7160869854","doi":"https://doi.org/10.48550/arxiv.2605.06957","title":"Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents","display_name":"Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160869854","doi":"https://doi.org/10.48550/arxiv.2605.06957"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06957","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":null,"license_id":null,"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.2605.06957","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037217032","display_name":"Shirin Sohrabi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sohrabi, Shirin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089233397","display_name":"Haritha Ananthakrishnan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ananthakrishnan, Haritha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025268861","display_name":"Harsha Kokel","orcid":"https://orcid.org/0000-0002-7548-3719"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kokel, Harsha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085594669","display_name":"Kavitha Srinivas","orcid":"https://orcid.org/0000-0003-4610-967X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srinivas, Kavitha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135893847","display_name":"Michael Katz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katz, Michael","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":0.3634999990463257,"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":0.3634999990463257,"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":0.2304999977350235,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.06530000269412994,"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/reuse","display_name":"Reuse","score":0.7791000008583069},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.7718999981880188},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.684499979019165},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.6141999959945679},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5932000279426575},{"id":"https://openalex.org/keywords/reusability","display_name":"Reusability","score":0.4546000063419342},{"id":"https://openalex.org/keywords/automated-planning-and-scheduling","display_name":"Automated planning and scheduling","score":0.4350000023841858}],"concepts":[{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.7791000008583069},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.7718999981880188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7124000191688538},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.684499979019165},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6141999959945679},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5932000279426575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5852000117301941},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4684999883174896},{"id":"https://openalex.org/C137981799","wikidata":"https://www.wikidata.org/wiki/Q1369184","display_name":"Reusability","level":3,"score":0.4546000063419342},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C2779436431","wikidata":"https://www.wikidata.org/wiki/Q30672407","display_name":"Policy learning","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C124527596","wikidata":"https://www.wikidata.org/wiki/Q17029359","display_name":"Hierarchical control system","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25839999318122864}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06957","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.06957","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06957","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":null,"license_id":null,"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":{"We":[0,53],"present":[1],"a":[2,46],"dynamic":[3,109],"policy-learning":[4],"approach":[5,82],"that":[6,30,120],"combines":[7],"generalized":[8],"planning":[9,122],"and":[10,35,69,89,134],"hierarchical":[11],"task":[12,33],"decomposition":[13],"for":[14,22,49,131],"LLM-based":[15],"agents.":[16],"Our":[17],"method,":[18],"Hierarchical":[19],"Component":[20],"Learning":[21],"Generalized":[23],"Policies":[24],"(HCL-GP":[25],"),":[26],"learns":[27],"parameterized":[28],"policies":[29],"generalize":[31],"across":[32],"instances":[34],"automatically":[36],"extracts":[37],"reusable":[38],"components":[39,59,65],"from":[40],"successful":[41],"executions,":[42],"organizing":[43],"them":[44],"into":[45],"component":[47],"library":[48],"compositional":[50],"policy":[51],"generation.":[52],"address":[54],"three":[55],"challenges:":[56],"(1)":[57],"learning":[58],"through":[60],"automated":[61],"decomposition,":[62],"(2)":[63],"generalizing":[64],"to":[66],"maximize":[67],"reuse,":[68],"(3)":[70],"efficient":[71],"retrieval":[72],"via":[73],"semantic":[74],"search.":[75],"Evaluated":[76],"on":[77,86,91,103],"the":[78],"AppWorld":[79],"benchmark,":[80],"our":[81],"achieves":[83],"98.2%":[84],"accuracy":[85,133],"normal":[87],"tasks":[88,93],"97.8%":[90],"challenge":[92],"with":[94,128],"unseen":[95],"applications,":[96],"improving":[97],"15.8":[98],"points":[99],"over":[100],"static":[101],"synthesis":[102],"challenging":[104],"scenarios.":[105],"For":[106],"open-source":[107],"models,":[108],"reuse":[110],"enables":[111],"62.5%":[112],"success":[113],"versus":[114],"near-zero":[115],"without":[116],"reuse.":[117],"This":[118],"demonstrates":[119],"classical":[121],"concepts":[123],"can":[124],"be":[125],"effectively":[126],"integrated":[127],"LLM":[129],"agents":[130],"improved":[132],"efficiency.":[135]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-12T00:00:00"}