Decision support for rule, and technique discovery in an uncertain environment

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, game theory, and fuzzy linear and nonlinear programming have been developed that allow the automatic inversion of rules from data bases. The rules discovered are shown to be 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 given.