Machine Learning of Parameter Control Doctrine for Sensor and Communication Systems
Abstract
Artificial intelligence approaches to learning were reviewed for their potential contributions to the construction of a system to learn parameter control doctrine. Separate learning tasks were isolated and several levels of related problems were distinguished. Formulas for providing the learning system with measures of its performance were derived for four kinds of targets.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1988
- Accession Number
- ADA200096
Entities
People
- R. A. Dillard
- R. B. Kamen