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Learning sensor-detection policies

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3 Author(s)
Malhotra, R. ; WL-AACF, WPAFB, OH, USA ; Blasch, E.P. ; Johnson, J.D.

Tactical aircraft pilots frequently perform complex sequential support tasks to obtain accurate and timely integrated sensor information about the local environment. When workloads are heavy, offloading these sensor-support tasks to an automated sensor management system would enhance performance and situational awareness. Reinforcement learning, a family of machine learning techniques, offers a way to learn to conduct sensor-support tasks despite sensor complexities by mapping a situation to an action. This paper applies reinforcement learning to a simplified target-detection policy, compares simulated performances of the learned technique to that of an optimal and an uninformed detection policy, and draws conclusions for future research directions

Published in:

Aerospace and Electronics Conference, 1997. NAECON 1997., Proceedings of the IEEE 1997 National  (Volume:2 )

Date of Conference:

14-18 Jul 1997