Standpoint Logics with Defeasible Beliefs

Nicholas LeisegangNicholas Leisegang, Thomas MeyerThomas Meyer, Sebastian RudolphSebastian Rudolph

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Nicholas Leisegang, Thomas Meyer, Sebastian Rudolph
Standpoint Logics with Defeasible Beliefs
In Ana Ozaki, Nico Potyka, eds., Proceedings of the 24th International Workshop on Non-Monotonic Reasoning (NMR 2025), CEUR, to appear

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KurzfassungAbstract
In this paper, we integrate the defeasible logic of Kraus, Lehmann and Magidor (KLM) with the standpoint logic framework of Gómez Álvarez and Rudolph. This is done with the goal of formally expressing knowledge taking into account multiple (possibly contradicting) viewpoints, which in turn may hold defeasible beliefs. In doing so, we utilise Defeasible Restricted Standpoint Logics (DRSL), introduced by Leisegang et al. Our work expands on previous work by providing a foundational representation result for DRSL semantics and systematically lifting several well-known entailment relations from the propositional case to the standpoint-enhanced setting. In particular, we characterise the semantics for DRSL through a set of KLM-style postulates adapted for the standpoints case. We furthermore provide a means to lift preferential entailment, and the class of entailment relations based on single ranking functions from the purely propositional to the standpoint-enhanced context, including rational and lexicographic closure. We show this can be done equivalently through semantic and algorithmic means. Furthermore, we show that, for each considered form of entailment, the complexity class of entailment checking does not change when moving from propositional KLM to DRSL.
Projekt:Project: SECAI, ScaDS.AI
Forschungsgruppe:Research Group: Computational LogicComputational Logic

@inproceedings{LMR2026,
  author    = {Nicholas Leisegang and Thomas Meyer and Sebastian Rudolph},
  title     = {Standpoint Logics with Defeasible Beliefs},
  editor    = {Ana Ozaki and Nico Potyka},
  booktitle = {Proceedings of the 24th International Workshop on Non-Monotonic
               Reasoning (NMR 2025)},
  series    = {CEUR},
  year      = {2026}
}