Abstract
For efficient implementation of Evolutionary Algorithms (EA) to a desktop grid computing environment, we propose a new generation alternation model called Grid-Oriented-Deletion (GOD) based on comparison with the conventional techniques. In previous research, generation alternation models are generally evaluated by using test functions. However, their exploration performance on the real problems such as Evolutionary Robotics (ER) has not been made very clear yet. Therefore we investigate the relationship between the exploration performance of EA on an ER problem and its generation alternation model. We applied four generation alternation models to the Evolutionary Multi-Robotics (EMR), which is the package-pushing problem to investigate their exploration performance. The results show that GOD is more effective than the other conventional models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Harvey, I., Husbands, P., Clif, D., Thompson, A., Jakobi, N.: Evolutionary Robotics: the Sussex Approach, Robotics and Autonomous Systems (1997)
Harvey, I., Thompson, A.: Through the Labyrinth Evolution Finds a Way: A Silicon Ridge. In: Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware, pp. 406–422. Springer, Heidelberg (1996)
Katada, Y., Ohkura, K., Ueda, K.: Measuring Neutrality of Fitness Landscapes Based on the Nei’s Standard Genetic Distance. In: Proceedings of 2003 Asia Pacific Symposium on Intelligent and Evolutionary Systems: Technology and Applications, pp. 107–114 (2003)
Foster, I., Kesselman, C.: The grid: blueprint for a new computing infrastructure. Morgan Kaufmann Publishers Inc., San Francisco (1998)
Schwefel, H.-P.: Evolution and Optimum Seeking. John Wiley & Sons, Chichester (1995)
Syswerda, G.: Uniform Crossover in Genetic Algorithms. In: Proceedings of the third international conference on Genetic algorithms, pp. 2–9 (1989)
Sato, H., Yamamura, M., Kobayashi, S.: Minimal generation gap model for GAs considering both exploration and exploitation. In: Proceedings of 4th International Conference on Soft Computing, pp. 494–497 (1996)
Yao, X., Liu, Y.: Fast Evolution Strategies. Control and Cybernetics 26(3), 467–496 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Tokyo
About this paper
Cite this paper
Oiso, M., Matsumura, Y., Yasuda, T., Ohkura, K. (2010). Evaluation of Generation Alternation Models in Evolutionary Robotics. In: Peper, F., Umeo, H., Matsui, N., Isokawa, T. (eds) Natural Computing. Proceedings in Information and Communications Technology, vol 2. Springer, Tokyo. https://doi.org/10.1007/978-4-431-53868-4_31
Download citation
DOI: https://doi.org/10.1007/978-4-431-53868-4_31
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-53867-7
Online ISBN: 978-4-431-53868-4
eBook Packages: Computer ScienceComputer Science (R0)