Whitley, D., T. Starkweather , and C. Bogart. 1990. Genetic algorithm s and neural networks: Optimizing connections and connectivity. Parallel Computing 14:347361.  Home/Search   Document Not in Database   Summary   Related Articles

....upon which a GA operates can take a variety of forms. The choice of an appropriate structure for a particular problem is a major factor in determining a GA s success. Structures utilized in prior research include binary strings (Goldberg, 1989) computer programs (Koza, 1992) neural networks (Whitley et al. 1990), and if then rules (Bauer, 1994) We first examine how a traditional GA performs optimization. In optimization, the goal is ideally to find the best possible solution to a problem. For real world problems, one does not usually know the best possible solution. Therefore, a more realistic ....

....of optimizing any classification structure or set of structures. In fact, people have tried optimizing most traditional machine learning structures as well as some nontraditiona l structures using GAs. These structures have ranged from neural network weights and topologies (Gruau Whitley, 1993; Whitley et al. 1990, 1991, 1993; Whitley Schaffer, 1992) to LISP programs (Koza, 1992) to regions of the instance space similar to decision trees induced by a splitting algorithm (Rendell, 1983, 1985; Sikora Shaw, 1994) to expertsystem rules (Montana, 1990) to weights for a game s evaluation function ....

Whitley, D., T. Starkweather , and C. Bogart. 1990. Genetic algorithm s and neural networks: Optimizing connections and connectivity. Parallel Computing 14:347361.

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