AIJun 12, 2021

Multi-Context Systems: Dynamics and Evolution (Pre-Print of "Multi-context systems in dynamic environments")

arXiv:2106.06780v16 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for more adaptable MCS in computational logic for distributed systems, but it appears incremental as it builds on existing MCS frameworks.

The paper tackles the problem of enhancing flexibility and generality in Multi-Context Systems (MCS) by introducing formal extensions for bridge-rules definition and application, aiming to improve their practical use in dynamic environments.

Multi-Context Systems (MCS) model in Computational Logic distributed systems composed of heterogeneous sources, or "contexts", interacting via special rules called "bridge rules". In this paper, we consider how to enhance flexibility and generality in bridge-rules definition and application. In particular, we introduce and discuss some formal extensions of MCSs useful for a practical use in dynamic environments, and we try to provide guidelines for implementations

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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