Measuring Resemblances Between Swarm Behaviours: A Perceptual Tolerance Near Set Approach

Issue title: Swarm Intelligence

Article type: Research Article

Authors: Ramanna, Sheela | Meghdadi, Amir H.

Affiliations: Department of Applied Computer Science, University of Winnipeg Winnipeg, Manitoba R3B 2E9 Canada. E-mail: [email protected] | Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Manitoba Winnipeg, Manitoba R3T 5V6 Canada. E-mail: [email protected]

Abstract: The problem considered in this article is how to detect and measure resemblances between swarm behaviours. The solution to this problem stems from an extension of recent work on tolerance near sets and image correspondence. Instead of considering feature extraction from subimages in digital images, we compare swarm behaviours by considering feature extraction from subsets of tuples of feature-values representing the behaviour of observed swarms of organisms. Thanks to recent work on the foundations of near sets, it is possible to formulate a rigorous approach to measuring the extent that swarm behaviours resemble each other. Fundamental to this approach is what is known as a recent description-based set intersection, a set containing objects with matching or almost the same descriptions extracted from objects contained in pairs of disjoint sets. Implicit in this work is a new approach to comparing information tables representing N. Tinbergen's ethology (study of animal behaviour) and direct result of recent work on what is known as rough ethology. Included in this article is a comparison of recent nearness measures that includes a new form of F. Hausdorff's distance measure. The contribution of this article is a tolerance near set approach to measuring the degree of resemblance between swarm behaviours.

Keywords: Ethology, near sets, nearness measure, rough ethology, swarm behaviour, tolerance space

DOI: 10.3233/FI-2009-163

Journal: Fundamenta Informaticae, vol. 95, no. 4, pp. 533-552, 2009