@ARTICLE { Rsds2471,
author = {Peters, James F.}, 
title = {Rough Ethology: Towards a Biologically-Inspired Study of Collective Behavior in Intelligent Systems with Approximation Spaces}, 
journal = {Transactions on Rough Sets}, 
number = 	{(no. III)}, 
volume = 3, 
pages = {153--174}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2005, 
url = {http://www.springer.de}, 
issn = {0302-9743}, 
isbn = {3-540-25998-8}, 
abstract = {This article introduces an ethological approach to evaluating biologically-inspired collective behavior in intelligent systems. This is made possible by considering ethology (ways to explain agent behavior) in the context of approximation spaces. The aims and methods of ethology in the study of the behavior of biological organisms were introduced by Niko Tinbergen in 1963. The rough set approach introduced by Zdzislaw Pawlak provides a ground for concluding to what degree a particular behavior for an intelligent system is a part of a set of behaviors representing a norm or standard. A rough set approach to ethology in studying the behavior of cooperating agents is introduced. Approximation spaces are used to derive action-based reference rewards for a swarm. Three different approaches to projecting rewards are considered as a part of a study of learning in real-time by a swarm. The contribution of this article is the introduction of an approach to rewarding swarm behavior in the context of an approximation space.}, 
keywords = {approximation space, behavior, ethology, intelligent systems, learning, rough sets, swarm, }, 
}