To fulfill the need for a good intelligent health system supproting medical staff by decision making, many new techniques for intelligent systems design has been introduced in the medical field. In ...accordance with recent trends, autonomous agents have been proposed as a promising approach to solve the problem. In the paper we present a new try: designing intelligent system with automatic programming empoying multiple autonomous agents (construcion and deconstruction agents named ADD, DELETE and MUTATE, generalization agents named JOIN and DISJOIN, and controllign agents named PROTECT and UNPROTECT) and software complexity metric to control the evolution of the system. Each agent changes the properties of evolving decision graph maximizing its accuracy, sensitivity, specificity and information density. The main objective of our approach is to make the learning process more flexible and robust and thereafter, hopefully, more successful.
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