By Topic

Evolving aggregation behaviors for swarm robotic systems: a systematic case study

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Bahgeci, E. ; Dept. of Comput. Eng., Middle East Tech. Univ., Ankara, Turkey ; Sahin, E.

When one attempts to use artificial evolution to develop behaviors for a swarm robotic system, he is faced with decisions to be made regarding the parameters of the evolution. In this paper, aggregation behavior is chosen as a case, where performance and scalability of aggregation behaviors of perceptron controllers that are evolved for a simulated swarm robotic system are systematically studied with different parameter settings. Four experiments are conducted varying some of the parameters, and rules of thumb are derived, which can be of guidance to the use of evolutionary methods to generate other swarm robotic behaviors.

Published in:

Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE

Date of Conference:

8-10 June 2005