Optimal Planning with Global Numerical State Constraints

Optimal Planning with Global Numerical State Constraints. Ivankovic, F., Haslum, P., Thiebaux, S., Shivashankar, V., & Nau, D. In Proceedings of the International Conference on Automated Planning and Scheduling, volume 24, pages 145–153, May, 2014.

Paper doi abstract bibtex

Automating the operations of infrastructure networks such as energy grids and oil pipelines requires a range of planning and optimisation technologies. However, current planners face signiﬁcant challenges in responding to this need. Notably, they are unable to model and reason about the global numerical state constraints necessary to capture ﬂows and similar physical phenomena occurring in these networks. A single discrete control action can affect the ﬂow throughout the network in a way that may depend on the entire network topology. Determining whether preconditions, goals and invariant conditions are satisﬁed requires solving a system of numerical constraints after each action application. This paper extends domain-independent optimal planning to this kind of reasoning. We present extensions of the formalism, relaxed plans, and heuristics, as well as new search variants and experimental results on two problem domains.

@inproceedings{ivankovic_optimal_2014,
	title = {Optimal {Planning} with {Global} {Numerical} {State} {Constraints}},
	volume = {24},
	url = {https://ojs.aaai.org/index.php/ICAPS/article/view/13648},
	doi = {10.1609/icaps.v24i1.13648},
	abstract = {Automating the operations of infrastructure networks such as energy grids and oil pipelines requires a range of planning and optimisation technologies. However, current planners face signiﬁcant challenges in responding to this need. Notably, they are unable to model and reason about the global numerical state constraints necessary to capture ﬂows and similar physical phenomena occurring in these networks. A single discrete control action can affect the ﬂow throughout the network in a way that may depend on the entire network topology. Determining whether preconditions, goals and invariant conditions are satisﬁed requires solving a system of numerical constraints after each action application. This paper extends domain-independent optimal planning to this kind of reasoning. We present extensions of the formalism, relaxed plans, and heuristics, as well as new search variants and experimental results on two problem domains.},
	language = {en},
	urldate = {2022-12-22},
	booktitle = {Proceedings of the {International} {Conference} on {Automated} {Planning} and {Scheduling}},
	author = {Ivankovic, Franc and Haslum, Patrik and Thiebaux, Sylvie and Shivashankar, Vikas and Nau, Dana},
	month = may,
	year = {2014},
	pages = {145--153},
}

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