AI Bibliography
AI Bibliography |
|
 |
 |
 |
|
Liles IV, J. M. (2021). Improving air battle management target assignment processes via approximate dynamic programming AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH. |
| Resource type: Report/Documentation BibTeX citation key: LilesIV2021 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, Engineering, General, Military Science Subcategories: Big data, Command and control, Decision making, Deep learning, Drones, Machine learning, Networked forces, Psychology of human-AI interaction, Situational cognition Creators: Liles IV Publisher: AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH Collection: |
| Attachments |
| Abstract |
|
Military air battle managers face many challenges when directing operations in quickly evolving combat scenarios. These scenarios require rapid decisions to engage moving and unpredictable targets. In defensive operations, the success of a sequence of air battle management decisions is reflected by the friendly forces ability to maintain air superiority by defending friendly assets. We develop a Markov decision process MDP model of the air battle management ABMproblem, wherein a set of unmanned combat aerial vehicles UCAV is tasked to defend a central asset from cruise missiles that arrive stochastically over time.
|