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Title: | Evolutionary computation variants for cooperative spatial coordination |
Authors: | Yannakakis, Georgios N. Levine, John Hallam, John |
Keywords: | Evolutionary computation Neural networks (Computer Science) Computer games |
Issue Date: | 2005-09 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Yannakakis, G. N., Hallam, J., & Levine, J. (2005). Evolutionary computation variants for cooperative spatial coordination. Congress on Evolutionary Computation, 2005. CEC2005. Vol. 3. IEEE, Edinburgh, Scotland. 2715-2722. |
Abstract: | This paper presents a comparative study between genetic and probabilistic search approaches of evolutionary computation. They are both applied for optimizing the behavior of multiple neural-controlled homogeneous agents whose spatial coordination tasks can only be successfully achieved through emergent cooperation. Both approaches demonstrate effective solutions of high performance; however, the genetic search approach appears to be both more robust and computationally preferred for this multi-agent case study. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/29479 |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Evolutionary_computation_variants_for_cooperative_spatial_coordination_2005.pdf | 189.19 kB | Adobe PDF | View/Open |
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