{"id":"https://openalex.org/W7160840768","doi":"https://doi.org/10.48550/arxiv.2605.07584","title":"Parallel Lifted Planning via Semi-Naive Datalog Evaluation","display_name":"Parallel Lifted Planning via Semi-Naive Datalog Evaluation","publication_year":2026,"publication_date":"2026-05-08","ids":{"openalex":"https://openalex.org/W7160840768","doi":"https://doi.org/10.48550/arxiv.2605.07584"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.07584","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07584","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.2605.07584","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135892325","display_name":"Dominik Drexler","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Drexler, Dominik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120411397","display_name":"Oliver Joergensen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joergensen, Oliver","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5031089257","display_name":"Jendrik Seipp","orcid":"https://orcid.org/0000-0002-2498-8020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seipp, Jendrik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":0.9735999703407288,"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":0.9735999703407288,"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":0.0052999998442828655,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.0052999998442828655,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/datalog","display_name":"Datalog","score":0.9293000102043152},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5855000019073486},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5848000049591064},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.5008000135421753},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.4629000127315521},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4625000059604645},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.451200008392334},{"id":"https://openalex.org/keywords/successor-cardinal","display_name":"Successor cardinal","score":0.41019999980926514},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.3889999985694885}],"concepts":[{"id":"https://openalex.org/C148230440","wikidata":"https://www.wikidata.org/wiki/Q1172264","display_name":"Datalog","level":2,"score":0.9293000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8116999864578247},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5855000019073486},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5848000049591064},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.542900025844574},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.451200008392334},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.4359000027179718},{"id":"https://openalex.org/C75306776","wikidata":"https://www.wikidata.org/wiki/Q7632662","display_name":"Successor cardinal","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40070000290870667},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C146834321","wikidata":"https://www.wikidata.org/wiki/Q2979672","display_name":"Closure (psychology)","level":2,"score":0.38280001282691956},{"id":"https://openalex.org/C167729594","wikidata":"https://www.wikidata.org/wiki/Q17736","display_name":"Axiom","level":2,"score":0.3758000135421753},{"id":"https://openalex.org/C164155591","wikidata":"https://www.wikidata.org/wiki/Q2067766","display_name":"Satisfiability modulo theories","level":2,"score":0.3625999987125397},{"id":"https://openalex.org/C2777035058","wikidata":"https://www.wikidata.org/wiki/Q1662634","display_name":"Clique","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C81721847","wikidata":"https://www.wikidata.org/wiki/Q163468","display_name":"Prolog","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28369998931884766},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C6943359","wikidata":"https://www.wikidata.org/wiki/Q875276","display_name":"Boolean satisfiability problem","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C2776235265","wikidata":"https://www.wikidata.org/wiki/Q18392052","display_name":"Fragment (logic)","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.07584","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07584","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.2605.07584","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.07584","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":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6440241932868958}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Lifted":[0],"classical":[1,36],"planners":[2,23],"operate":[3],"directly":[4],"on":[5,98,131,145,149,179],"first-order":[6],"planning":[7,18],"tasks":[8,127,147],"to":[9,104,175],"avoid":[10],"the":[11,54,117,129,136,153,161],"computationally":[12],"demanding":[13],"grounding":[14,84],"step.":[15],"However,":[16],"lifted":[17,35],"is":[19,156],"typically":[20],"slower,":[21],"as":[22,39,139],"must":[24],"repeatedly":[25],"instantiate":[26],"ground":[27],"structures":[28],"during":[29],"search.":[30],"Many":[31],"core":[32],"components":[33],"of":[34,56,64,79,152,170],"planning,":[37],"such":[38],"successor":[40],"generation,":[41],"axiom":[42],"evaluation,":[43],"task":[44],"grounding,":[45],"and":[46,66,71,83,135],"delete-relaxed":[47],"heuristics,":[48],"have":[49],"previously":[50],"been":[51],"studied":[52],"through":[53],"lens":[55],"Datalog":[57,107,159],"evaluation.":[58,108],"We":[59,86],"build":[60],"upon":[61],"this":[62,89],"line":[63],"work":[65],"extend":[67,103],"it":[68],"by":[69],"developing":[70],"analyzing":[72],"an":[73,166],"execution":[74,163],"model":[75,164],"with":[76,94,116],"two":[77],"levels":[78],"parallelism:":[80],"rule-level":[81],"parallelism":[82],"parallelism.":[85],"further":[87],"specialize":[88],"solver":[90],"for":[91],"planning-specific":[92],"workloads":[93],"a":[95,132,176],"grounder":[96],"based":[97],"clique":[99],"enumeration,":[100],"which":[101],"we":[102],"support":[105],"semi-naive":[106],"Our":[109],"experimental":[110],"evaluation":[111],"using":[112],"greedy":[113],"best-first":[114],"search":[115],"FF":[118],"heuristic":[119],"shows":[120],"that":[121],"our":[122],"implementation":[123],"already":[124],"solves":[125],"more":[126],"than":[128],"baselines":[130],"single":[133],"core,":[134],"gap":[137],"widens":[138],"additional":[140],"cores":[141,181],"are":[142],"used.":[143],"Moreover,":[144],"hard-to-ground":[146],"where":[148],"average":[150,167],"97.6%":[151],"total":[154],"runtime":[155],"spent":[157],"in":[158,182],"execution,":[160],"proposed":[162],"exhibits":[165],"parallel":[168],"fraction":[169],"92.4%,":[171],"while":[172],"achieving":[173],"up":[174],"6-fold":[177],"speedup":[178],"8":[180],"practice.":[183]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-12T00:00:00"}