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  1. Swarm Intelligence
  2. Swarm Intelligence : Volume 8
  3. Swarm Intelligence : Volume 8, Issue 2, June 2014
  4. Interactive ant colony optimization (iACO) for early lifecycle software design
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Swarm Intelligence : Volume 11
Swarm Intelligence : Volume 10
Swarm Intelligence : Volume 9
Swarm Intelligence : Volume 8
Swarm Intelligence : Volume 8, Issue 4, December 2014
Swarm Intelligence : Volume 8, Issue 3, September 2014
Swarm Intelligence : Volume 8, Issue 2, June 2014
AutoMoDe: A novel approach to the automatic design of control software for robot swarms
Revisiting wavefront construction with collective agents: an approach to foraging
Interactive ant colony optimization (iACO) for early lifecycle software design
Swarm Intelligence : Volume 8, Issue 1, March 2014
Swarm Intelligence : Volume 7
Swarm Intelligence : Volume 6
Swarm Intelligence : Volume 5
Swarm Intelligence : Volume 4
Swarm Intelligence : Volume 3
Swarm Intelligence : Volume 2
Swarm Intelligence : Volume 1

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Interactive ant colony optimization (iACO) for early lifecycle software design

Content Provider SpringerLink
Author Simons, Christopher L. Smith, Jim White, Paul
Copyright Year 2014
Abstract Finding good designs in the early stages of the software development lifecycle is a demanding multi-objective problem that is crucial to success. Previously, both interactive and non-interactive techniques based on evolutionary algorithms (EAs) have been successfully applied to assist the designer. However, recently ant colony optimization was shown to outperform EAs at optimising quantitative measures of software designs with a limited computational budget. In this paper, we propose a novel interactive ACO (iACO) approach, in which the search is steered jointly by an adaptive model that combines subjective and objective measures. Results show that iACO is speedy, responsive and effective in enabling interactive, dynamic multi-objective search. Indeed, study participants rate the iACO search experience as compelling. Moreover, inspection of the learned model facilitates understanding of factors affecting users’ judgements, such as the interplay between a design’s elegance and the interdependencies between its components.
Starting Page 139
Ending Page 157
Page Count 19
File Format PDF
ISSN 19353812
Journal Swarm Intelligence
Volume Number 8
Issue Number 2
e-ISSN 19353820
Language English
Publisher Springer US
Publisher Date 2014-06-19
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Ant colony optimization Software design Interactive search Artificial Intelligence (incl. Robotics) Computer Systems Organization and Communication Networks ApplicationMathematics/Computational Methods of Engineering Communications Engineering, Networks Computer Communication Networks
Content Type Text
Resource Type Article
Subject Artificial Intelligence
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