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Complexity of Qualitative Timeline-Based Planning

Authors Dario Della Monica , Nicola Gigante , Salvatore La Torre , Angelo Montanari

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Author Details

Dario Della Monica
  • University of Udine, Italy
Nicola Gigante
  • University of Udine, Italy
Salvatore La Torre
  • University of Salerno, Italy
Angelo Montanari
  • University of Udine, Italy

Funding

The authors acknowledge the partial support by the Italian INdAM-GNCS project Ragionamento Strategico e Sintesi Automatica di Sistemi Multi-Agente. Nicola Gigante and Angelo Montanari are partially supported by the PRID project ENCASE - Efforts in the uNderstanding of Complex interActing SystEms.

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Dario Della Monica, Nicola Gigante, Salvatore La Torre, and Angelo Montanari. Complexity of Qualitative Timeline-Based Planning. In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 16:1-16:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.TIME.2020.16

Abstract

The timeline-based approach to automated planning was originally developed in the context of space missions. In this approach, problem domains are expressed as systems consisting of independent but interacting components whose behaviors over time, the timelines, are governed by a set of temporal constraints, called synchronization rules. Although timeline-based system descriptions have been successfully used in practice for decades, the research on the theoretical aspects only started recently. In the last few years, some interesting results have been shown concerning both its expressive power and the computational complexity of the related planning problem. In particular, the general problem has been proved to be EXPSPACE-complete. Given the applicability of the approach in many practical scenarios, it is thus natural to ask whether computationally simpler but still expressive fragments can be identified. In this paper, we study the timeline-based planning problem with the restriction that only qualitative synchronization rules, i.e., rules without explicit time bounds in the constraints, are allowed. We show that the problem becomes PSPACE-complete.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Temporal reasoning
Keywords
  • Timeline-based planning
  • qualitative temporal constraints
  • complexity

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