dc.contributor.convenor | Amedeo Cesta and Ioannis Refanidis | |
dc.contributor.author | Robinson, N | |
dc.contributor.author | Gretton, C | |
dc.contributor.author | Pham, DN | |
dc.contributor.author | Sattar, A | |
dc.contributor.editor | Gerevini, Alfonso | |
dc.contributor.editor | Howe, Adele | |
dc.contributor.editor | Cesta, Amedeo | |
dc.contributor.editor | Refanidis, Ioannis | |
dc.date.accessioned | 2017-05-03T14:38:43Z | |
dc.date.available | 2017-05-03T14:38:43Z | |
dc.date.issued | 2009 | |
dc.date.modified | 2010-10-13T10:03:40Z | |
dc.identifier.isbn | 9781577354062 | |
dc.identifier.refuri | http://icaps09.icaps-conference.org/ | |
dc.identifier.uri | http://hdl.handle.net/10072/31985 | |
dc.description.abstract | Planning based on propositional SAT(isfiability) is a powerful approach to computing step-optimal plans given a parallel execution semantics. In this setting: (i) a solution plan must be minimal in the number of plan steps required, and (ii) non-conflicting actions can be executed instantaneously in parallel at a plan step. Underlying SAT-based approaches is the invocation of a decision procedure on a SAT encoding of a bounded version of the problem. A fundamental limitation of existing approaches is the size of these encodings. This problem stems from the use of a direct representation of actions - i.e. each action has a corresponding variable in the encoding. A longtime goal in planning has been to mitigate this limitation by developing a more compact split - also termed lifted - representation of actions in SAT encodings of parallel step-optimal problems. This paper describes such a representation. In particular, each action and each parallel execution of actions is represented uniquely as a conjunct of variables. Here, each variable is derived from action pre and post-conditions. Because multiple actions share conditions, our encoding of the planning constraints is factored and relatively compact. We find experimentally that our encoding yields a much more efficient and scalable planning procedure over the state-of-the-art in a large set of planning benchmarks. | |
dc.description.peerreviewed | Yes | |
dc.description.publicationstatus | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | AAAI Press | |
dc.publisher.place | Menlo Park, California | |
dc.publisher.uri | http://icaps09.icaps-conference.org/ | |
dc.relation.ispartofstudentpublication | Y | |
dc.relation.ispartofconferencename | International Conference on Automated Planning and Scheduling (ICAPS-09) | |
dc.relation.ispartofconferencetitle | ICAPS 2009 - Proceedings of the 19th International Conference on Automated Planning and Scheduling | |
dc.relation.ispartofdatefrom | 2009-09-19 | |
dc.relation.ispartofdateto | 2009-09-23 | |
dc.relation.ispartoflocation | Thessaloniki, Greece | |
dc.relation.ispartofpagefrom | 281 | |
dc.relation.ispartofpageto | 288 | |
dc.rights.retention | Y | |
dc.subject.fieldofresearch | Artificial intelligence not elsewhere classified | |
dc.subject.fieldofresearchcode | 460299 | |
dc.title | SAT-Based Parallel Planning Using a Split Representation of Actions | |
dc.type | Conference output | |
dc.type.description | E1 - Conferences | |
dc.type.code | E - Conference Publications | |
gro.faculty | Griffith Sciences, School of Information and Communication Technology | |
gro.date.issued | 2009 | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Sattar, Abdul | |