The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Planning Through Stochastic Local Search and Temporal Action Graphs in LPG
Open accessAbstract
We present some techniques for planning in domains specified with the recent standard language PDDL2.1, supporting 'durative actions' and numerical quantities. These techniques are implemented in LPG, a domain-independent planner that took part in the 3rd International Planning Competition (IPC). LPG is an incremental, any time system producing multi-criteria quality plans. The core of the system is based on a stochastic local search method and on a graph-based representation called 'Temporal Action Graphs' (TA-graphs). This paper focuses on temporal planning, introducing TA-graphs and proposing some techniques to guide the search in LPG using this representation. The experimental results of the 3rd IPC, as well as further results presented in this paper, show that our techniques can be very effective. Often LPG outperforms all other fully-automated planners of the 3rd IPC in terms of speed to derive a solution, or quality of the solutions that can be produced.
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Cites
Maintaining knowledge about temporal intervals
Allen, J. F. (1983) · Communications of the ACM · doi:10.1145/182.358434 · Cited by 7,593 · cited 3×
“Finally, other dire tions for improving temporal planning in lpg on ern the treatmentof a ri her temporal representation to handle upper and lower bounds on the possible a tiondurations, as well as the integration of temporal reasoning te hniques to deal with temporal onstraints between a tions similar to those that a…”
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Cited by
The 2014 International Planning Competition: Progress and Trends
Vallati, M., Chrpa, L., Grześ, M., McCluskey, T. L., Roberts, M., & Sanner, S. (2015) · AI Magazine · doi:10.1609/aimag.v36i3.2571 · Cited by 112
The deterministic part of the seventh International Planning Competition
Linares López, C., Jiménez Celorrio, S., & García Olaya, Á. (2015) · Artificial Intelligence · doi:10.1016/j.artint.2015.01.004 · Cited by 71
Adapting an AI Planning Heuristic for Directed Model Checking
Kupferschmid, S., Hoffmann, J., Dierks, H., & Behrmann, G. (2006) · Lecture Notes in Computer Science · doi:10.1007/11691617_3 · Cited by 50
Metadata
- Authors
- Gerevini, A., Saetti, A., & Serina, I.
- Venue
- Journal of Artificial Intelligence Research
- Publisher
- AI Access Foundation
- Published
- 2003-12-01
- Volume
- 20
- Pages
- 239-290
- ISSN
- 1076-9757 (ISSN-L)
- OpenAlex
- W1827139443
- Cited by
- 318
- References
- 1
- FWCI
- 20.14
- Type
- journal article
- Language
- en
- Open access
- diamond
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