John R. McDonnell

Learn More
This paper presents a new approach to genetic algorithm based machine learning. We use genetic algorithms augmented with a case-based memory of past problem solving attempts to obtain better performance over time on sets of similar problems. Rather than starting anew on each problem, we periodically inject a genetic algorithm's population with appropriate(More)
We investigate the use of case injection to bias the results of a genetic algorithm (GA) in two scenarios. First, when the problem we are attempting to bias by case injection is identical to the problem from which the injected cases were gathered. Second, when the problem we are attempting to bias is different (to varying degree) from the problem from which(More)
Tactical air command and control systems must consider a multitude of environmental and operational conditions when reassigning assets, which often results in a lengthy decision process. This paper presents a suite of tools that are intended to compress the kill-chain by providing support for the planning and reassignment of tactical air strike assets.(More)
This work addresses a decision support system that can be used for effectively re-tasking TACAIR assets under a variety of constraints. Analysis of the common operational picture provides augmented situational awareness. Automatic risk analysis keeps the user aware of current and planned risk levels to blue force assets. Options for reacting to changes in(More)