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  1. Axiomatic theory of betweenness.Sanaz Azimipour & Pavel Naumov - 2020 - Archive for Mathematical Logic 60 (1):227-239.
    Betweenness as a relation between three individual points has been widely studied in geometry and axiomatized by several authors in different contexts. The article proposes a more general notion of betweenness as a relation between three sets of points. The main technical result is a sound and complete logical system describing universal properties of this relation between sets of vertices of a graph.
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  • On interchangeability of Nash equilibria in multi-player strategic games.Pavel Naumov & Brittany Nicholls - 2013 - Synthese 190 (S1):1-22.
    The article studies properties of interchangeability of pure, mixed, strict, and strict mixed Nash equilibria. The main result is a sound and complete axiomatic system that describes properties of interchangeability in all four settings. It has been previously shown that the same axiomatic system also describes properties of independence in probability theory, nondeducibility in information flow, and non-interference in concurrency theory.
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  • Independence in Information Spaces.Pavel Naumov - 2012 - Studia Logica 100 (5):953-973.
    Three different types of interdependence between pieces of information, or "secrets", are discussed and compared. Two of them, functional dependence and non-deducibility, have been studied and axiomatized before. This article introduces a third type of interdependence and provides a complete and decidable axiomatization of this new relation.
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  • The Ryōan-ji axiom for common knowledge on hypergraphs.Jeffrey Kane & Pavel Naumov - 2014 - Synthese 191 (14):3407-3426.
    The article studies common knowledge in communication networks with a fixed topological structure. It introduces a non-trivial principle, called the Ryōan-ji axiom, which captures logical properties of common knowledge of all protocols with a given network topology. A logical system, consisting of the Ryōan-ji axiom and two additional axioms, is proven to be sound and complete.
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  • Fault tolerance in belief formation networks.Sarah Holbrook & Pavel Naumov - 2012 - In Luis Farinas del Cerro, Andreas Herzig & Jerome Mengin (eds.), Logics in Artificial Intelligence. Springer. pp. 267--280.
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