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Many complex problems can be solved by a sequence of steps or simple heuristics. In many cases a good solution relies on both good heuristics and proper ordering of their application. Problems such as creating a constrained path through a graph can be solved in this way if we can find a mechanism for ordering the heuristics. We propose using a genetic(More)
This paper presents our design philosophy for robotic teams involved in distributed exploratory missions, such as military reconnaissance, scientiic exploration , and security patrols. It outlines the fundamental requirements of these mission types, nds commonalities among them, analyzes the roles robots can play, and notes research areas requiring greater(More)
— If evaluation of individuals in an evolutionary environment is expensive relative to the rest of the evolutionary process, maximizing the amount learned from each evaluation becomes more important. In this paper, we describe a new crossover operator for genetic programming, memetic crossover, that allows individuals to imitate the observed success of(More)
We describe a variety of projects developed as part of a course in Artiicial Intelligence at the University of Minnesota. The projects cover navigation of small mobile robots and learning to accomplish simple tasks, and require a variety of approaches from neural networks to genetic programming to reactive behaviors. The projects have all been implemented(More)