ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Quotient Evolutionary Space: Abstraction of Evolutionary process w.r.t macroscopic properties

Dukkipati, Ambedkar and Murty, Narasimha M and Bhatnagar, Shalabh (2003) Quotient Evolutionary Space: Abstraction of Evolutionary process w.r.t macroscopic properties. In: The 2003 Congress on Evolutionary Computation – CEC 2003, 8-12 December 2003, Canberra, Australia, pp. 846-853.

[img]
Preview
PDF
quotient-t.pdf

Download (1510Kb)

Abstract

Darwinian evolution, which is characterized in terms of particular macroscopic behavior that emerges from microscopic organismic interaction, considers populations as units of evolutionary change. We formalize these concepts in evolutionary computation by developing notion of quotient evolutionary space(Q.E.S). We map set of all finite populations to a set of macroscopic properties of population those are chosen a prior;; and we call this mapping as evolufionary criteria. On the ‘quotient set of populations’ that is induced by evolutionary criteria, we define mathematical structures to define evolutionary change with respect to chosen macroscopic parameters at populational level. This allows us to transform the objective defined on the search space that is imposed by the fitness function to an objective on the population space. We call quotient set of populations along with the mathematical structures the quotient evolutionary space. To demonstrate the abstraction we consider fitness distribution of population as evolutionary criteria and give a detailed analysis of resulting spaces and basic convergence results.

Item Type: Conference Paper
Additional Information: ©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 25 Aug 2008
Last Modified: 19 Sep 2010 04:12
URI: http://eprints.iisc.ernet.in/id/eprint/331

Actions (login required)

View Item View Item