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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Zhang Ma, D. Hong-Jun Zhang Wang, B.-L. Yun-Tao Chen |
| Copyright Year | 2003 |
| Description | Author affiliation: Comput. Sch., Huazhong Univ. of Sci. & Technol., Hubei, China (Wei Zhang; Ma, D.; Hong-Jun Zhang) |
| Abstract | Simulation modeling the battlefield scenario should provide a realistic training ground for the soldiers where it is possible to test the soldiers' skills in a variety of situations. The design of opponents is one of significant facts to influence train level in battlefield simulation. This paper endeavors to show how method as multipopulation genetic algorithms can be used to address the problems such as how to make opponents' actions and strategies unpredictable and how to make battlefield simulation circumstance more realistic. Multipopulation genetic algorithms' inherent optimizing characteristic in subpopulations is just adaptive to solving our problem. The origin of this work is in the area of military training in battlefield simulation. |
| Sponsorship | IEEE Systems Man and Cybernetics Tech. Committee on Cybernetics, Hebei Univ. Northwestern Polytechnical Univ |
| Starting Page | 1704 |
| Ending Page | 1707 |
| File Size | 252461 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780381319 |
| DOI | 10.1109/ICMLC.2003.1259771 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2003-11-05 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic algorithms Computational modeling Computer simulation Military computing Evolution (biology) Testing Equations Aerospace simulation Weather forecasting Application software |
| Content Type | Text |
| Resource Type | Article |
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