Decision Support for Rule, Technique and Strategy Discovery in a Multi-Agent Environment

摘要

For many applications it is desirable to construct expert systems to be used as decision aids. It is often essential that the algorithm make decisions at least at the quality level of the best human experts according to some measure. The algorithm should not only incorporate human expertise and its related uncertainty, but also be able to exploit an opponent's uncertainty. In many instances, due to newly emerging paradigms, the necessary human expertise does not exist. Approaches based on fuzzy logic, fuzzy number theory, evolutionary algorithms, and fuzzy linear and nonlinear programming have been developed that allow the automatic inversion of rules from data bases. The rules discovered are equivalent to rules already developed by human experts or in the case, where no human being has expertise to be original. Along with the theoretical basis, an application to electronic warfare, and related experimental results are discussed.