Synthesis of Timeline-Based Planning Strategies Avoiding Determinization
Renato Acampora (University of Udine, Italy), Dario Della Monica, (University of Udine, Italy), Luca Geatti (University of Udine, Italy),, Nicola Gigante (Free University of Bozen-Bolzano, Italy), Angelo Montanari, (University of Udine, Italy), Pietro Sala (University of Verona

TL;DR
This paper introduces a method to synthesize planning strategies for timeline-based models without needing automaton determinization, by identifying a large fragment that maps directly to deterministic automata.
Contribution
It identifies a large fragment of timeline-based planning where plan-existence reduces to deterministic automata nonemptiness, enabling strategy synthesis without determinization.
Findings
A large fragment of planning models can be directly mapped to deterministic automata.
A maximal subset of Allen's relations fits into this deterministic fragment.
The approach simplifies strategy synthesis for timeline-based planning.
Abstract
Qualitative timeline-based planning models domains as sets of independent, but interacting, components whose behaviors over time, the timelines, are governed by sets of qualitative temporal constraints (ordering relations), called synchronization rules. Its plan-existence problem has been shown to be PSPACE-complete; in particular, PSPACE-membership has been proved via reduction to the nonemptiness problem for nondeterministic finite automata. However, nondeterministic automata cannot be directly used to synthesize planning strategies as a costly determinization step is needed. In this paper, we identify a large fragment of qualitative timeline-based planning whose plan-existence problem can be directly mapped into the nonemptiness problem of deterministic finite automata, which can then be exploited to synthesize strategies. In addition, we identify a maximal subset of Allen's…
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