基于细胞自动机的多尺度空间推理

Abstract

This paper proposes a novel approach to multi-scale spatial reasoning by leveraging cellular automata (CA) systems. The core idea is to simulate systems with local interactions, effectively mimicking processes that occur across multiple spatial scales. We introduce a framework where different CA rules are designed to represent behaviors at varying scales. Cell interactions and diffusion are then utilized to extract spatial features and generate predictions from multi-scale spatial data, such as images and geographic datasets. The novelty lies in the integration of CA models with multi-scale analysis, offering a fresh perspective for analyzing complex spatial phenomena. The system is designed to provide a flexible framework for data analysis without requiring extensive prior knowledge. The presented methodology offers a computational approach for simulating and interpreting spatial patterns that are difficult to discern through traditional analytical methods. This approach provides a theoretical foundation and a computational tool for understanding spatial dynamics.