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20232026
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cs.AI2026

Incremental LTLf Synthesis

Giuseppe De Giacomo, Yves Lespérance, Gianmarco Parretti +2

In this paper, we study incremental LTLf synthesis -- a form of reactive synthesis where the goals are given incrementally while in execution. In other words, the protagonist agent…

cs.AI2025

LTLf Adaptive Synthesis for Multi-Tier Goals in Nondeterministic Domains

Giuseppe De Giacomo, Gianmarco Parretti, Shufang Zhu

We study a variant of LTLf synthesis that synthesizes adaptive strategies for achieving a multi-tier goal, consisting of multiple increasingly challenging LTLf objectives in nondet…

cs.AI2024

Computational Grounding of Responsibility Attribution and Anticipation in LTLf

Giuseppe De Giacomo, Emiliano Lorini, Timothy Parker +1

Responsibility is one of the key notions in machine ethics and in the area of autonomous systems. It is a multi-faceted notion involving counterfactual reasoning about actions and…

cs.AI2023

LTLf Best-Effort Synthesis in Nondeterministic Planning Domains

Giuseppe De Giacomo, Gianmarco Parretti, Shufang Zhu

We study best-effort strategies (aka plans) in fully observable nondeterministic domains (FOND) for goals expressed in Linear Temporal Logic on Finite Traces (LTLf). The notion of…

cs.AI2023

Symbolic LTLf Best-Effort Synthesis

Giuseppe De Giacomo, Gianmarco Parretti, Shufang Zhu

We consider an agent acting to fulfil tasks in a nondeterministic environment. When a strategy that fulfills the task regardless of how the environment acts does not exist, the age…