Evolving Multi Rover Systems in Dynamic and Noisy Environments-Reference-Cited by-同舟云学术

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Evolving Multi Rover Systems in Dynamic and Noisy Environments

Published:2007 Issue: Volume: Page:371-387
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
Short-container-title:

Author:

Tumer Kagan,Agogino Adrian

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-49774-5_16.pdf

Reference17 articles.

1. A. Agah and G. A. Bekey. A genetic algorithm-based controller for decentralized multi-agent robotic systems. In In Proc. of the IEEE International Conference of Evolutionary Computing, Nagoya, Japan, 1996.

2. A. Agogino, K. Stanley, and R. Miikkulainen. Online interactive neuroevolution. Neural Processing Letters, 11: 29-38, 2000.

3. A. Agogino and K. Tumer. Efficient evaluation functions for multi-rover systems. In The Genetic and Evolutionary Computation Conference, pages 1-12, Seatle, WA, June 2004.

4. T. Balch. Behavioral diversity as multiagent cooperation. In Proc. of SPIE’99 Workshop on Multiagent Systems, Boston, MA, 1999.

5. G. Baldassarre, S. Nolfi, and D. Parisi. Evolving mobile robots able to display collective behavior. Artificial Life, 9: 255-267, 2003.

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