Abstract
We present a novel semantics for the language of multi-agent only believing exploiting belief bases, and show how to use it for automatically checking formulas of this language. We provide a PSPACE algorithm for model checking relying on a reduction to QBF, an implementation and some experimental results on computation time in a concrete example.
This work is partially supported by the project epiRL (“Epistemic Reinforcement Learning”) ANR-22-CE23-0029, the project CoPains (“Cognitive Planning in Persuasive Multimodal Communication”) ANR-18-CE33-0012 and the AI Chair project Responsible AI (ANR-19-CHIA-0008) both from the French National Agency of Research. Support from the Natural Intelligence Toulouse Institute (ANITI) is also gratefully acknowledged.
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Notes
- 1.
As usual, the difference between knowledge and belief lies in the fact that the former is always correct while the latter can be incorrect.
- 2.
The extended version of this paper, including proofs and examples, is available at ArXiv: https://arxiv.org/abs/2307.14893.
- 3.
Available at https://src.koda.cnrs.fr/tiago.de.lima/lda/.
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Lima, T.d., Lorini, E., Schwarzentruber, F. (2023). Base-Based Model Checking for Multi-agent only Believing. In: Gaggl, S., Martinez, M.V., Ortiz, M. (eds) Logics in Artificial Intelligence. JELIA 2023. Lecture Notes in Computer Science(), vol 14281. Springer, Cham. https://doi.org/10.1007/978-3-031-43619-2_30
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