Automated battlefield simulation command and control using artificial neural networks

Contemporary distributed interactive battle simulations are becoming increasingly large and complex and therefore difficult to manage. The success of future projects will depend in part on the ability to manage aspects of the command and control surfaces in an automated and highly predictable manner. Artificial intelligence in general and artificial neural networks (ANNs) in particular offer attractive mechanisms to automate command and control. This paper describes the linear interactive activation and competition model ANN, a highspeed, object-oriented model, for use in several battle simulations and has demonstrated that this is a feasible application of the technology.<>