  Normally a decision support system is build to solve problem where
multi-criteria decisions are involved. The knowledge base is the vital part of
the decision support containing the information or data that is used in
decision-making process. This is the field where engineers and scientists have
applied several intelligent techniques and heuristics to obtain optimal
decisions from imprecise information. In this paper, we present a hybrid
neuro-genetic learning approach for the adaptation a Mamdani fuzzy inference
system for the Tactical Air Combat Decision Support System (TACDSS). Some
simulation results demonstrating the difference of the learning techniques and
are also provided.
