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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hicks, J.D. Stoyen, A.D. Quiming Zhu |
| Copyright Year | 2001 |
| Description | Author affiliation: Nebraska Univ., Omaha, NE, USA (Hicks, J.D.) |
| Abstract | In the highly dynamic and information rich environment of military submarine operations, the Commanding Officer must make split second decisions that could ultimately result in the destruction or survival of Ownship or the accomplishment of its designated mission. Despite extensive training and expertise, the fog of war often shadows real world encounters. Pieces of the tactical puzzle may be scattered, broken, and/or even missing. It is the Commanding Officer's job to meld the fog into a clear tactical picture and intuitively decide upon the optimal course of action to obtain his mission goals and objectives. A mathematically derived optimal solution could be used as a decision making aid for the Commanding Officer to enhance Ownship's performance. A highly innovative hybrid Bayesian/differential game modeling approach is being developed to tackle this problem. The resulting theory and technology will facilitate tactical operations by addressing such practical problems as tradeoff evaluation for course of action and maintaining tactical advantage while avoiding counter detection. |
| Sponsorship | IEEE Comput. Soc. Tech. Committee on Complexity in Comput. |
| Starting Page | 200 |
| Ending Page | 210 |
| File Size | 1253298 |
| Page Count | 11 |
| File Format | |
| ISBN | 0769511597 |
| DOI | 10.1109/ICECCS.2001.930179 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-06-11 |
| Publisher Place | Sweden |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Intelligent agent Software architecture Uncertainty Underwater vehicles Decision making Game theory Scattering Bayesian methods Software testing Data analysis |
| Content Type | Text |
| Resource Type | Article |
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