A Compositional Sheaf-Theoretic Framework for Event-Based Systems

2020/05/31 by Gioele Zardini, David I. Spivak, Andrea Censi +1
Computer Science · Engineering · Mathematics · #Advanced Memory and Neural Computing #Artificial intelligence #Complex system #Computer science #Distributed systems and fault tolerance #Event (particle physics) #Formalism (music) #Mathematics #Modular Robots and Swarm Intelligence #Physics #Principle of compositionality #Pure mathematics #Sheaf #Theoretical computer science #cs.RO #cs.SY #eess.SP #eess.SY #math.CT

paper · pdf · doi:10.4204/eptcs.333.10

published as EPTCS 333, 2021, pp. 139-153 · 24 pages

openalex created_date 2020/05/13 · arxiv created 2020/06/22 · openalex publication_date 2021/01/19 · arxiv updated 2021/03/09 · openalex updated_date 2026/08/05

Abstract

A compositional sheaf-theoretic framework for the modeling of complex event-based systems is presented. We show that event-based systems are machines, with inputs and outputs, and that they can be composed with machines of different types, all within a unified, sheaf-theoretic formalism. We take robotic systems as an exemplar of complex systems and rigorously describe actuators, sensors, and algorithms using this framework.

Citations

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