Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
Adaptive Behavior
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (2)
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Scholes, S.
Right arrow Articles by Melhuish, C.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Comparisons in Evolution and Engineering: The Collective Intelligence of Sorting

Sam Scholes

Intelligent Autonomous Systems Lab, University of the West of England, Samuel2.Scholes{at}uwe.ac.uk

Matt Wilson

Intelligent Autonomous Systems Lab, University of the West of England, mathew.wilson{at}uwe.ac.uk

Ana B. Sendova-Franks

School of Mathematical Sciences and Intelligent Autonomous Systems Lab, University of the West of England, ab-sendovafranks{at}uwe.ac.uk

Chris Melhuish

Intelligent Autonomous Systems Lab, University of the West of Enfland, chris.melhuish{at}uwe.ac.uk

Collaboration between biologists and roboticists can facilitate the creation of new behavioral algorithms by roboticists and help biologists by exposing the underlying mechanisms that allow the algorithms to function (for a review see Webb, 2000). This paper makes a direct comparison between robot annular puck sorting using real robots (Wilson, Melhuish, Sendova-Franks & Scholes, 2004) and brood sorting in the ant Leptothorax albipennis (Franks & Sendova-Franks, 1992). We compared the ants’ and robots’ structures in terms of radial displacement, shape, compactness, completeness and separation. This showed the effectiveness and limitations of using metrics developed for robots to quantify structures built by ants and helped relate common aspects of the structures to possible common aspects of the underlying algorithms. The ant behavioral rule set is still under investigation and a better understanding of the structure it creates has proved a very useful tool to examine aspects of the algorithm. We draw the conclusions that firstly, the size of the area available for sorting affects the robot algorithm and ant algorithm in opposite ways, secondly, the metrics have proved very useful in aiding discrimination between the robot and ant structures and thirdly, application of the metrics to the ant structure has offered biologists new ideas and a better understanding of the structure and how it is built.

Key Words: puck sorting • brood sorting • sorting area • Leptothorax • ant • adaptiveness

Adaptive Behavior, Vol. 12, No. 3-4, 147-159 (2004)
DOI: 10.1177/105971230401200302
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 Adaptive BehaviorHome page
B. Webb
Animals Versus Animats: Or Why Not Model the Real Iguana?
Adaptive Behavior, August 1, 2009; 17(4): 269 - 286.
[Abstract] [PDF]