Efficiently Reasoning with Interval Constraints in Forward Search Planning

Abstract

In this paper we present techniques for reasoning natively with quantitative/qualitative interval constraints in statebased PDDL planners. While these are considered important in modeling and solving problems in timeline based planners; reasoning with these in PDDL planners has seen relatively little attention, yet is a crucial step towards making PDDL planners applicable in real-world scenarios, such as space missions. Our main contribution is to extend the planner OPTIC to reason natively with Allen interval constraints. We show that our approach outperforms both MTP, the only PDDL planner capable of handling similar constraints and a compilation to PDDL 2.1, by an order of magnitude. We go on to present initial results indicating that our approach is competitive with a timeline based planner on a Mars rover domain, showing the potential of PDDL planners in this setting.

On the Expressive Power of Intermediate and Conditional Effects in Temporal Planning

“…Following on from this last observation, in the future, we plan to empirically experiment with our compilations to evaluate the practical applicability on existing planners: this could open new venues for further research as the simultaneity constraints we used as a basis for our compilation could be in principle natively supported, hence providing a more efficient implementation of the ideas behind our encodings. Other directions of research include the analysis of other planning features such as the quantitative Allenalgebra constraints identified in (Coles et al 2019). Speaking of Allen relations, it comes natural to see whether our constructions can be used to support a kind of temporally extended goals where, instead of LTL conditions, more expressive interval conditions can be expressed, for example in terms of (some fragment of) the Halpern and Shoham interval temporal logic (Della Monica et al 2011).…”

“…Our construction is also related to a compilation of quantitative Allen relations presented in (Coles et al 2019); in fact, our simultaneity operators can be seen as starts-with, ends-with or meets Allen constraints depending on the kind of clip actions involved. We remark that all previous compilations are limited to the -separation semantics, while our approach works with or without this assumption.…”

Efficient Temporal Planning Using Metastates

“…Such a constraint representation need not be limited to temporal relations. In the future, we hope to apply our approach to other expressive planning models in-cluding hybrid numeric planning, PDDL3 preference models (Gerevini et al 2009), and planning with richer temporal relations such as interval constraints (Coles et al 2019).…”