Collective specialization for evolutionary design of a multi-robot system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4433 LNCS, Issue , 2007, Pages 189-205

  Eiben, Agoston E ^a   Nitschke, Geoff S ^a   Schut, Martijn C ^a  

^a VU UNIVERSITY AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; HEURISTIC ALGORITHMS; MULTI AGENT SYSTEMS; NEURAL NETWORKS; PARAMETER ESTIMATION;

CONTROLLER DESIGN; NOVEL NEURO EVOLUTION;

ROBOTICS;

EID: 38049103443     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71541-2_13     Document Type: Conference Paper

References (18)

1. G. Baldassarre, S. Nolfi, and D. Parisi. Evolving mobile robots able to display collective behavior. Artificial Life, 9(1):255-267, 2003.
2. B. Bryant and R. Miikkulainen. Neuro-evolution for adaptive teams. In Proceedings of the 2003 Congress on Evolutionary Computation, pages 2194-2201. IEEE Press, Canberra, Australia, 2003.
3. L. Bull and J. Holland. Evolutionary computing in multi-agent environments: Eusociality. In Proceedings of the Second Annual Conference on Genetic Programming, pages 347-352. IEEE Press, San Francisco, USA., 1997.
4. A. Eiben and J. Smith. Introduction to Evolutionary Computing. Springer-Verlag, Berlin, Germany, 2003.
5. B. Flannery, S. Teukolsky, and W. Vetterling. Numerical Recipes. Cambridge University Press, Cambridge, 1986.
6. D. Floreano and J. Urzelai. Evolutionary robots with on-line self-organization and behavioral fitness. Neural Networks, 13(1):431-443, 2000.
7. J. Gaufrais, G. Theraulaz, J. Deneubourg, and C. Anderson. Emergent polyethism as a consequence of increased colony size in insect societies. Journal of Theoretical Biology, 215(1):363-373, 2002.
8. F. Gomez and R. Miikkulainen. Incremental evolution of complex general behavior. Adaptive Behavior, 5(1):317-342, 1997.
9. N. Jakobi, P. Husbands, and I. Harvey. Noise and the reality gap: The use of simulation in evolutionary robotics. In Proceedings of Third European Conference on Artificial Life (ECAL-95), pages 704-720. Springer-Verlag, Granada, Spain, 1995.
10. M. Kreiger and J. Billeter. The call of duty: Self-organized task allocation in a population of up to twelve mobile robots. Robotics and Autonomous Systems, 30: 65-84, 2000.
11. S. Nolfi and D. Floreano. Learning and evolution. Autonomous Robots, 7(1):89-113, 1999.
12. S. Nolfi and D. Parisi. Learning to adapt to changing environments in evolving neural networks. Adaptive Behavior, 1(5):75-98, 1997.
13. P. Paalanen, J. Kamarainen, J. Ilonen, and H. Kälviäinen. Feature representation and discrimination based on gaussian mixture model probability densities - practices and algorithms. Pattern Recognition, 39(7):1346-1358, 2006.
14. K. Stanley, B. Bryant, and R. Miikkulainen. Real-time neuro-evolution in the nero video game. IEEE Transactions Evolutionary Computation, 9(6):653-668, 2005.
15. K. Stanley and R. Miikkulainen. Competitive coevolution through evolutionary complexification. Journal of Artificial Intelligence Research, 21(1):63-100, 2004.
16. S. Thakoor. Bio-inspired engineering of exploration systems. Journal of Space Mission Architecture, 2(1):49-79, 2000.
17. S. Whiteson, N. Kohl, R. Miikkulainen, and P. Stone. Evolving keep-away soccer players through task decomposition. In Proceeding of the Genetic and Evolutionary Computation Conference, pages 356-368. AAAI Press, Chicago, 2003.
18. L. Young, E. Aiken, G. Briggs, V. Gulick, and R. Mancinelli. Rotorcraft as mars scouts. In Proceeding of the IEEE Aerospace Conference, pages 4-12. IEEE Press, Big Sky, USA, 2002.