Extracting Lifted Mutual Exclusion Invariants from Temporal Planning Domains

TL;DR

This paper introduces a novel method for automatically extracting mutual exclusion invariants from temporal planning domains, enhancing invariant detection by considering temporal interactions and improving planner efficiency.

Contribution

It extends existing invariant synthesis techniques to temporal domains, enabling the discovery of a broader set of invariants and reducing the number of state variables needed.

Findings

Broader invariants lead to fewer multi-valued state variables.

Fewer variables improve temporal planner performance.

The method effectively handles temporal and non-temporal domains.

Abstract

We present a technique for automatically extracting mutual exclusion invariants from temporal planning instances. It first identifies a set of invariant templates by inspecting the lifted representation of the domain and then checks these templates against properties that assure invariance. Our technique builds on other approaches to invariant synthesis presented in the literature, but departs from their limited focus on instantaneous actions by addressing temporal domains. To deal with time, we formulate invariance conditions that account for the entire structure of the actions and the possible concurrent interactions between them. As a result, we construct a significantly more comprehensive technique than previous methods, which is able to find not only invariants for temporal domains, but also a broader set of invariants for non-temporal domains. The experimental results reported in this paper provide evidence that identifying a broader set of invariants results in the generation of fewer multi-valued state variables with larger domains. We show that, in turn, this reduction in the number of variables reflects positively on the performance of a number of temporal planners that use a variable/value representation by significantly reducing their running time.