×

zbMATH — the first resource for mathematics

Book review of: P. Haslum et. al., An introduction to the planning domain definition language. (English) Zbl 1436.00014
Review of [Zbl 1434.68004].
MSC:
00A17 External book reviews
68-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68T30 Knowledge representation
Software:
PDDL
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Alford, R.; Kuter, U.; Nau, N., Translating HTNs to PDDL: a small amount of domain knowledge can go a long way, (Proceedings of the Twenty First International Joint Conference on Artificial Intelligence. Proceedings of the Twenty First International Joint Conference on Artificial Intelligence, IJCAI-2009 (2009)), 1629-1634
[2] Bernardini, S.; Fagnani, F.; Smith, D. E., Extracting mutual exclusion invariants from lifted temporal planning domains, Artif. Intell., 258, 1-65 (2018) · Zbl 1433.68404
[3] Coles, A.; Coles, A.; Martinez, M.; Savas, E.; Delfa, J.; de la Rosa, T.; E-Martin, Y.; Garcia-Olaya, A., Efficiently reasoning with interval constraints in forward search planning, (Proceedings of the Thirty Third National Conference on Artificial Intelligence. Proceedings of the Thirty Third National Conference on Artificial Intelligence, AAAI-2019 (2019), AAAI Press)
[4] Fikes, R.; Nilsson STRIPS, N., A new approach to the application of theorem proving to problem solving, (Proceedings of the 2nd International Joint Conference on Artificial Intelligence. Proceedings of the 2nd International Joint Conference on Artificial Intelligence, IJCAI-1971 (1971), Morgan Kaufmann Publishers Inc.), 608-620
[5] Fox, M.; Long, D., The automatic inference of state invariants in TIM, J. Artif. Intell. Res., 9, 367-421 (1998) · Zbl 0910.68199
[6] Fox, M.; Long, D., PDDL2.1: an extension to PDDL for expressing temporal planning domains, J. Artif. Intell. Res., 20, 61-124 (2003) · Zbl 1036.68093
[7] Fox, M.; Long, D., Modelling mixed discrete-continuous domains for planning, J. Artif. Intell. Res., 27, 235-297 (2006) · Zbl 1182.68238
[8] Gerevini, A.; Haslum, P.; Long, D.; Saetti, A.; Dimopoulos, Y., Deterministic planning in the fifth international planning competition: PDDL3 and experimental evaluation of the planners, Artif. Intell., 173, 5-6, 619-668 (2009) · Zbl 1191.68634
[9] Gerevini, A.; Kuter, U.; Nau, D.; Saetti, A.; Nathaniel, W., Combining domain-independent planning and HTN planning: the duet planner, (Proceedings of the Eighteenth European Conference on Artificial Intelligence. Proceedings of the Eighteenth European Conference on Artificial Intelligence, ECAI-2008 (2008)), 573-577
[10] Gerevini, A.; Schubert, L., Inferring state constraints for domain-independent planning, (Proceedings of the Fifteenth National Conference on Artificial Intelligence. Proceedings of the Fifteenth National Conference on Artificial Intelligence, AAAI-1998 (1998), AAAI Press/The MIT Press), 905-912
[11] Gerevini, A.; Schubert, L., Discoplan: an efficient on-line system for computing planning domain invariants, (Proceedings of the European Conference on Planning. Proceedings of the European Conference on Planning, ECP-2001 (2014), AAAI Press), 284-288
[12] Gerevini, A.; Schubert, L., Discovering state constraints for planning with conditional effects in discoplan (part I), Ann. Math. Artif. Intell. (2019), Printed version in press
[13] Ghallab, M.; Howe, A.; Knoblock, G.; McDermott, D.; Ram, A.; Veloso, M.; Weld, D.; Wilkins, D., PDDL - the planning domain definition language (1998), Yale Center for Computational Vision and Control, Technical Report CVC TR-98-003/DCS TR-1165
[14] Ghallab, M.; Laruelle, H., Representation and control in IxTeT, a temporal planner, (Proceedings of the Second International Conference on Artificial Intelligence Planning Systems. Proceedings of the Second International Conference on Artificial Intelligence Planning Systems, AIPS-1994 (1994), AAAI Press), 61-67
[15] Helmert, M., Concise finite-domain representations for PDDL planning tasks, Artif. Intell., 173, 5-6, 503-535 (2009) · Zbl 1191.68635
[16] Helmert, M.; Do, M.; Refanidis, I., Changes in PDDL 3.1 (2008), Technical report
[17] Hoffmann, J.; Edelkampi, E., The deterministic part of IPC-4: an overview, J. Artif. Intell. Res., 24, 519-579 (2005) · Zbl 1080.68669
[18] Micheli, A.; Scala, E., Temporal planning with metric trajectory constraints, (Proceedings of the Thirty Third National Conference on Artificial Intelligence. Proceedings of the Thirty Third National Conference on Artificial Intelligence, AAAI-2019 (2019), AAAI Press)
[19] Muscettola, B., HSTN: integrating planning and scheduling, (Zweben, M.; Fox, M., Intelligent Scheduling (1994), Morgan Kaufmann), 169-212, chapter 6
[20] Nebel, B., On the compilability and expressive power of propositional planning formalisms, J. Artif. Intell. Res., 12, 271-315 (2000) · Zbl 0943.68182
[21] Pednault, E., ADL: exploring the middle ground between STRIPS and the situation calculus, (Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning. Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, KR-1989 (1989)), 324-332
[22] Percassi, F.; Gerevini, A., On compiling away pddl3 soft trajectory constraints without using automata, (Proceedings of the Twenty Ninth International Conference on Automated Planning and Scheduling. Proceedings of the Twenty Ninth International Conference on Automated Planning and Scheduling, ICAPS-2019 (2019), AAAI Press)
[23] Wright, B.; Mattmüller, R.; Nebel, B., Compiling away soft trajectory constraints in planning, (Proceedings of the Sixteenth Conference on Principles of Knowledge Representation and Reasoning. Proceedings of the Sixteenth Conference on Principles of Knowledge Representation and Reasoning, KR-2018 (2018)), 474-482
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.