KR2026Proceedings of the 23rd International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 23rd International Conference on Principles of Knowledge Representation and Reasoning

Lisbon, Portugal. July 20-23, 2026.

Edited by
  1. Renata Wassermann
  2. Marie-Laure Mugnier
  3. Franz Baader

ISSN: 2334-1033
ISBN: 978-1-956792-18-8

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Published by

Copyright © 2026 International Joint Conferences on Artificial Intelligence Organization

Synthesis Foundations for Online LTLf Goal Management

  1. Giuseppe De Giacomo(University of Oxford, Sapienza University of Rome)
  2. Yves Lespérance(York University)
  3. Gianmarco Parretti(Sapienza University of Rome)
  4. Fabio Patrizi(Sapienza University of Rome)
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BibTeX
https://doi.org/10.24963/kr.2026/26

Keywords

  1. null-Linear Temporal Logic on Finite Traces (LTLf)
  2. null-Reactive synthesis
  3. null-Online Goal Management
  4. null-Agent Goal Management System
  5. null-Finite-State Automata
  6. null-LTLf Progression

Abstract

Autonomous agents' goals typically change as they operate. Handling this is particularly challenging when the environment is nondetermnistic and the goals are temporally extended. In this paper, we assume that the agent operates in a fully observable nondeterministic (FOND) domain and uses Linear Temporal Logic over finite traces (LTLf) to represent goals. We use LTLf synthesis notions to formalize this problem of online agent goal management, handling goal adoption, goal dropping, and performing steps of the synthesized strategy, while ensuring that the agent's goals always remain realizable. We propose automata-based and formula progression-based methods to manage LTLf goals. We implement these methods and evaluate their effectiveness experimentally.