Abstract
In AI planning, given the initial state, the goal state and a set of actions, a solution of the problem is a sequence of actions which takes the initial state to the goal state, i.e. a plan. The field has been studied and significantly improved since the past few years. Many state of the art planning systems, such as Graphplan, FF, GP-CSP, TGP, TPSYS, TP4, TLPlan, STAN, LPGP, have shown their good performance on different planning domains. Scientists continue studying to deal with bigger and more complex planning domains which include the explicit modelling of time, resources.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Blum, L., Furst, M.L.: Fast planning through Planning Graph Analysis. Artificial Intelligence 90, 281–300 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dinh, T.B. (2004). Solution Extraction with the “Critical Path” in Graphplan-Based Optimal Temporal Planning. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_72
Download citation
DOI: https://doi.org/10.1007/978-3-540-30201-8_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23241-4
Online ISBN: 978-3-540-30201-8
eBook Packages: Springer Book Archive