{"id":"https://openalex.org/W7135243329","doi":"https://doi.org/10.48550/arxiv.2603.11351","title":"Novelty Adaptation Through Hybrid Large Language Model (LLM)-Symbolic Planning and LLM-guided Reinforcement Learning","display_name":"Novelty Adaptation Through Hybrid Large Language Model (LLM)-Symbolic Planning and LLM-guided Reinforcement Learning","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135243329","doi":"https://doi.org/10.48550/arxiv.2603.11351"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11351","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11351","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129013604","display_name":"Hong Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lu, Hong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128928181","display_name":"Pierrick Lorang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lorang, Pierrick","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085692066","display_name":"Timothy R. Duggan","orcid":"https://orcid.org/0009-0007-6955-2961"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Duggan, Timothy R.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129034502","display_name":"Jivko Sinapov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinapov, Jivko","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5044523801","display_name":"Matthias Scheutz","orcid":"https://orcid.org/0000-0002-0064-2789"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Scheutz, Matthias","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5129013604"],"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":0.2662999927997589,"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":0.2662999927997589,"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":0.26030001044273376,"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":0.1014999970793724,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8282999992370605},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6771000027656555},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.5968000292778015},{"id":"https://openalex.org/keywords/automated-planning-and-scheduling","display_name":"Automated planning and scheduling","score":0.5160999894142151},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4722999930381775},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41269999742507935},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4122999906539917},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4023999869823456},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3617999851703644}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8282999992370605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7347000241279602},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6690999865531921},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.5968000292778015},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.5160999894142151},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4122999906539917},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4023999869823456},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34860000014305115},{"id":"https://openalex.org/C199190896","wikidata":"https://www.wikidata.org/wiki/Q3509276","display_name":"Learning classifier system","level":3,"score":0.33559998869895935},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.29510000348091125},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C13687954","wikidata":"https://www.wikidata.org/wiki/Q4826847","display_name":"Autonomous agent","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.26179999113082886},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11351","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.11351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11351","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":"article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5732069611549377}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,72],"dynamic":[1],"open-world":[2],"environments,":[3],"autonomous":[4],"agents":[5],"often":[6],"encounter":[7],"novelties":[8],"that":[9,36,53],"hinder":[10],"their":[11,18],"ability":[12],"to":[13,16,25,39,65,68,84,99],"find":[14],"plans":[15,27,89],"achieve":[17],"goals.":[19],"Specifically,":[20],"traditional":[21],"symbolic":[22,55,92],"planners":[23],"fail":[24],"generate":[26,88],"when":[28],"the":[29,34,46,76,82,91,101,116],"robot's":[30],"planning":[31],"domain":[32],"lacks":[33],"operators":[35],"enable":[37],"it":[38],"interact":[40],"appropriately":[41],"with":[42,90],"novel":[43,70],"objects":[44],"in":[45,105,119,127],"environment.":[47],"We":[48],"propose":[49],"a":[50,60],"neuro-symbolic":[51],"architecture":[52],"integrates":[54],"planning,":[56],"reinforcement":[57,102],"learning,":[58],"and":[59,95],"large":[61],"language":[62],"model":[63],"(LLM)":[64],"learn":[66],"how":[67],"handle":[69],"objects.":[71],"particular,":[73],"we":[74],"leverage":[75],"common":[77],"sense":[78],"reasoning":[79],"capability":[80],"of":[81],"LLM":[83],"identify":[85],"missing":[86],"operators,":[87],"AI":[93],"planner,":[94],"write":[96],"reward":[97],"functions":[98],"guide":[100],"learning":[103,106,126],"agent":[104],"control":[107],"policies":[108],"for":[109],"newly":[110],"identified":[111],"operators.":[112],"Our":[113],"method":[114],"outperforms":[115],"state-of-the-art":[117],"methods":[118],"operator":[120,125],"discovery":[121],"as":[122,124],"well":[123],"continuous":[128],"robotic":[129],"domains.":[130]},"counts_by_year":[],"updated_date":"2026-03-14T06:46:50.379900","created_date":"2026-03-14T00:00:00"}
