Symbolic Pattern Temporal Numeric Planning with Intermediate Conditions and Effects
Matteo Cardellini, Enrico Giunchiglia

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 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 one can specify plan's conditions/effects that must be checked/applied at specific times during the plan execution. Experimental results…
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Taxonomy
TopicsAI-based Problem Solving and Planning · Robotic Path Planning Algorithms · Formal Methods in Verification
