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| A computational-intelligence-based optimization of agents' initial positions in land combat simulation | |
| 作者姓名： | WU Chunguo LIANG Yanchun GE Hongwei CAO Lijuan LEE Heow Pueh |
| 作者单位： | College of Computer Science and Technology, Jilin University, Changchun 130012, China; Institute of High Performance Computing, Singapore 117528, Singapore,College of Computer Science and Technology, Jilin University, Changchun 130012, China; Institute of High Performance Computing, Singapore 117528, Singapore,College of Mathematics Science, Jilin University, Changchun 130012, China,Institute of High Performance Computing, Singapore 117528, Singapore,Institute of High Performance Computing, Singapore 117528, Singapore; Department of Mechanical Engineering, National University of Singapore, Singapore 119260, Singapore |
| 基金项目： | Supported by the Key Project of National Education Ministry of China (Grant No. 02090) |
| 摘 要： | The optimization of agents' initial properties enables agents to perform their assigned tasks more perfectly. This paper presents an optimizing method using the combination of radial basis function (RBF) neural network and genetic algorithm (GA). In the land combat simulation, the method can ensure that the agents optimized defeat the agents not optimized absolutely. Compared with the optimization based on support vector machines (SVM), the proposed method improves the efficiency more than twenty times, so it suits the cases where the speed as well as performance is required. |
| 关 键 词： | multi-agent system RBF neural network support vector machine land combat simulation genetic algo |
A computational-intelligence-based optimization of agents' initial positions in land combat simulation |
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| WU Chunguo,LIANG Yanchun,GE Hongwei,CAO Lijuan,LEE Heow Pueh.A computational-intelligence-based optimization of agents'' initial positions in land combat simulation[J].Progress in Natural Science,2003,13(8):620-625. | |
| Authors: | WU Chunguo LIANG Yanchun GE Hongwei CAO Lijuan LEE Heow Pueh |
| Affiliation: | 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China; Institute of High Performance Computing, Singapore 117528, Singapore 2. College of Mathematics Science, Jilin University, Changchun 130012, China 3. Institute of High Performance Computing, Singapore 117528, Singapore 4. Institute of High Performance Computing, Singapore 117528, Singapore; Department of Mechanical Engineering, National University of Singapore, Singapore 119260, Singapore |
| Abstract: | The optimization of agents' initial properties enables agents to perform their assigned tasks more perfectly. This paper presents an optimizing method using the combination of radial basis function (RBF) neural network and genetic algorithm (GA). In the land combat simulation, the method can ensure that the agents optimized defeat the agents not optimized absolutely. Compared with the optimization based on support vector machines (SVM), the proposed method improves the efficiency more than twenty times, so it suits the cases where the speed as well as performance is required. |
| Keywords: | multi-agent system RBF neural network support vector machine land combat simulation genetic algo |
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