Symbolic Pattern Temporal Numeric Planning with Intermediate Conditions and Effects

TL;DR

This paper extends the Symbolic Pattern Planning approach to handle temporal planning with durative actions, intermediate conditions/effects, and specific timing constraints, improving planning efficiency and applicability in real-world scenarios.

Contribution

It introduces an extension of SPP to the ICE fragment, enabling effective temporal planning with overlapping actions and timed conditions/effects, and demonstrates superior performance in various domains.

Findings

Outperforms existing planners in non-ICE temporal domains

Achieves comparable results with state-of-the-art in ICE domains

Excels in a real-world application domain

Abstract

Recently, a Symbolic Pattern Planning (SPP) approach was proposed for numeric planning where a pattern (i.e., a finite sequence of actions) suggests a causal order between actions. The pattern is then encoded in a SMT formula whose models correspond to valid plans. If the suggestion by the pattern is inaccurate and no valid plan can be found, the pattern is extended until it contains the causal order of actions in a valid plan, making the approach complete. In this paper, we extend the SPP approach to the temporal planning with Intermediate Conditions and Effects (ICEs) fragment, where $(i)$ actions are durative (and thus can overlap over time) and have conditions/effects which can be checked/applied at any time during an action's execution, and $(ii)$ one can specify plan's conditions/effects that must be checked/applied at specific times during the plan execution. Experimental results show that our SPP planner Patty $(i)$ outperforms all other planners in the literature in the majority of temporal domains without ICEs, $(ii)$ obtains comparable results with the SoTA search planner for ICS in literature domains with ICEs, and $(iii)$ outperforms the same planner in a novel domain based on a real-world application.