Abstract
This paper describes a polynomial algorithm for preprocessing planning problems which contain domain axioms (DAs) in the form p 1 ^ p 2 ^ ... ^ p n → c. The algorithm presented is an improved version of the (incorrect) transformation for DAs described by Gazen and Knoblock in [6].
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Blum, A. L., Furst, M. L. (1997) “Fast Planning Through Planning Graph Analysis”, Artificial Intelligence, 90:281–300.
Chapman, D. (1987) “Planning for Conjunctive Goals”, Artificial Intelligence, 32(3):333–377.
Fikes, R.E., Nilsson, N.J. (1971) “STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving”, Artificial Intelligence, 2:189–208.
Garagnani, M. (2000) “Speaker-hearer beliefs for discourse planning”, Proceedings of the 17th International Conference on Artificial Intelligence (ICAI’00), Las Vegas, Nevada, June 2000.
Garagnani, M. (1999) “A sound Linear Algorithm for Pre-processing planning problems with Language Axioms”, Proceedings of PLANSIG-99, Manchester, England.
Gazen, B.C., Knoblock, C.A. (1997) “Combining the Expressivity of UCPOP with the Efficiency of Graphplan”, Proceedings ECP-97, Toulouse, France.
Koehler, J., Nebel, B., Hoffmann, J., Dimopoulos, Y. (1997) “Extending Planning Graphs to an ADL Subset”, Proceedings ECP-97, Toulouse, France.
Penberthy, J. S., Weld, D. (1992) “UCPOP: A Sound, Complete, Partial-order Planner for ADL”, Proceedings of the International Workshop on Knowledge Representation (KR-9), pp.103–114.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag London
About this paper
Cite this paper
Garagnani, M. (2001). A Correct Algorithm for Efficient Planning with Preprocessed Domain Axioms. In: Bramer, M., Preece, A., Coenen, F. (eds) Research and Development in Intelligent Systems XVII. Springer, London. https://doi.org/10.1007/978-1-4471-0269-4_26
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0269-4_26
Publisher Name: Springer, London
Print ISBN: 978-1-85233-403-1
Online ISBN: 978-1-4471-0269-4
eBook Packages: Springer Book Archive