English

A Logic of Secrecy on Simplicial Models

Logic in Computer Science 2026-04-06 v1 Logic

Abstract

We develop a logic of secrecy on simplicial models for multi-agent systems. Standard simplicial models provide a geometric semantics for knowledge by representing global states as facets of a chromatic simplicial complex and agents' local states as coloured vertices. However, secrecy cannot in general be captured as a genuinely new modality by relying on the ordinary simplicial knowledge structure alone. This motivates the introduction of an additional secrecy layer. To this end, we define \emph{simplicial secrecy models}, which enrich standard simplicial epistemic models with agent-relative secrecy neighborhood functions attached to local states. On this basis, we introduce a primitive secrecy operator SaφS_a\varphi. Semantically, SaφS_a\varphi holds when agent aa knows φ\varphi in the ordinary simplicial sense and, moreover, the truth set of φ\varphi belongs to one of the designated secrecy neighborhoods associated with aa's current local state. The clause for secrecy thus combines an ordinary knowledge requirement with an additional local-state-based neighborhood requirement, while the frame condition ensures that designated secrecy events remain non-trivial from the perspective of every other agent. We formulate a system SSL\mathsf{SSL} for the resulting language and show that it is sound with respect to the class of simplicial secrecy models. For the genuinely multi-agent case A2|A|\ge 2, we prove completeness by first constructing an auxiliary-colour canonical model and then representing it inside the original class of pure AA-chromatic simplicial secrecy models. The resulting framework yields a primitive, local-state-based, and geometrically grounded account of secrecy on simplicial models, together with a sound axiomatization and, in the genuinely multi-agent case, a complete one.

Cite

@article{arxiv.2604.02673,
  title  = {A Logic of Secrecy on Simplicial Models},
  author = {Shanxia Wang},
  journal= {arXiv preprint arXiv:2604.02673},
  year   = {2026}
}

Comments

This is a preliminary draft. Comments and suggestions are very welcome

R2 v1 2026-07-01T11:52:16.193Z