LinGraph: a graph-based automated planner for concurrent task planning based on linear logic

dc.citation.epage934en_US
dc.citation.issueNumber3en_US
dc.citation.spage914en_US
dc.citation.volumeNumber47en_US
dc.contributor.authorKortik S.en_US
dc.contributor.authorSaranli, U.en_US
dc.date.accessioned2018-04-12T10:37:23Z
dc.date.available2018-04-12T10:37:23Z
dc.date.issued2017en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractIn this paper, we introduce an automated planner for deterministic, concurrent domains, formulated as a graph-based theorem prover for a propositional fragment of intuitionistic linear logic, relying on the previously established connection between intuitionistic linear logic and planning problems. The new graph-based theorem prover we introduce improves planning performance by reducing proof permutations that are irrelevant to planning problems particularly in the presence of large numbers of objects and agents with identical properties (e.g. robots within a swarm, or parts in a large factory). We first present our graph-based automated planner, the Linear Logic Graph Planner (LinGraph). Subsequently we illustrate its application for planning within a concurrent manufacturing domain and provide comparisons with four existing automated planners, BlackBox, Symba-2, Metis and the Temporal Fast Downward (TFD), covering a wide range of state-of-the-art automated planning techniques and implementations. We show that even though LinGraph does not rely on any heuristics, it still outperforms these systems for concurrent domains with large numbers of identical objects and agents. These gains persist even when existing methods on symmetry reduction and numerical fluents are used, with LinGraph capable of handling problems with thousands of objects. Following these results, we also show that plan construction with LinGraph is equivalent to multiset rewriting systems, formally relating LinGraph to intuitionistic linear logic. © 2017, Springer Science+Business Media New York.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T10:37:23Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2017en
dc.identifier.doi10.1007/s10489-017-0936-xen_US
dc.identifier.issn0924-669Xen_US
dc.identifier.urihttp://hdl.handle.net/11693/36358en_US
dc.language.isoEnglishen_US
dc.publisherSpringer New York LLCen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s10489-017-0936-xen_US
dc.source.titleApplied Intelligence: the international journal of artificial intelligence, neural networks, and complex problem-solving technologiesen_US
dc.subjectAssembly planningen_US
dc.subjectAutomated planningen_US
dc.subjectLinear logicen_US
dc.subjectMultiset rewritingen_US
dc.subjectAutomationen_US
dc.subjectGraph theoryen_US
dc.subjectGraphic methodsen_US
dc.subjectLinear algebraen_US
dc.subjectNumerical methodsen_US
dc.subjectRobot programmingen_US
dc.subjectTheorem provingen_US
dc.subjectAssembly planningen_US
dc.subjectAutomated planningen_US
dc.subjectIntuitionistic linear logicen_US
dc.subjectITS applicationsen_US
dc.subjectLinear logicen_US
dc.subjectManufacturing domainsen_US
dc.subjectMultiset rewritingen_US
dc.subjectSymmetry reductionen_US
dc.subjectComputer circuitsen_US
dc.titleLinGraph: a graph-based automated planner for concurrent task planning based on linear logicen_US
dc.typeArticleen_US

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