Evolutionary Algorithms Fuzzy logic, developed in 1965 by Zadeh, is an extension of conventional set theory which allows computers to interpret the real world as humans would. Unfortunately not everything in life is precise. People express their their reasoning in terms of imprecise terms. For example one describes height as Tall or Short and not in precise terms such as 6 feet 4 inch. This sort of imprecise reasoning is the base for Fuzzy Logic.
Evolutionary algorithms are nondeterministic search methods based on the ideas of genetics.
EAs try to mimic the Darwinian theory of natural selection and evolution process, tending to evolve solutions to problems instead of trying to solve them directly. One of the EA's characteristics is the multiple points' search, which discriminates the EA from the other random search methods. That is, each string corresponds to a candidate of the optimal result in the search space and many such results exist in EA's search. This project is primarily concerned with the application of GAs to neurofuzzy control.