Title
Statistical Exploration of Distributed Pattern Formation Based on Minimalistic Approach
Abstract
In this paper, we discuss the pattern formation of objects that can be stacked and transported by distributed autonomous agents. Inspired by the social behavior of termite colonies, which often build elaborate three-dimensional structures (nest towers), this paper explores the mechanism of termite-like agents through a computational and minimalistic approach. We introduce a cellular automata model (i.e., spatially discretized) for the agents and the objects they can transport, where each agent follows a "rule" determined by the assignment of fundamental actions (move/ load/unload) based on the state of its neighboring cells. To evaluate the resulting patterns from the viewpoint of structural complexity and agent effort, we classify the patterns using the Kolmogorov dimension and higher-order local autocorrelation, two well-known statistical techniques in image processing. We find that the Kolmogorov dimension provides a good metric for the structural complexity of a pattern, whereas the higherorder local autocorrelation is an effective means of identifying particular local patterns.
Year
DOI
Venue
2019
10.20965/jrm.2019.p0905
JOURNAL OF ROBOTICS AND MECHATRONICS
Keywords
Field
DocType
multi-agent system,distributed pattern formation,cellular automata approach
Computer science,Multi-agent system,Pattern formation,Distributed computing
Journal
Volume
Issue
ISSN
31
SP6
0915-3942
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Yuichiro Sueoka124.84
Takamasa Tahara200.34
Masato Ishikawa315038.92
Koichi Osuka413242.74