David B. Fogel, Editor-in-chief

Evolutionary Computation: A New Transactions
Evolution is the primary unifying principle of modern biological thought. Classic Darwinian evolutionary theory, combined with the selectionism of Weismann and the genetics of Mendel, has now become a rather universally accepted set of arguments known as the neo-Darwinian paradigm [1]-[9]. Neo-Darwinism asserts that the history of the vast majority of life is fully accounted for by only a very few statistical processes acting on and within populations and species [10, p. 39]. These processes are reproduction, mutation, competition, and selection. Reproduction is an obvious behavioral property of all life. But similarly as obvious, mutation (i.e., genetic change) is guaranteed in any system that continuously reproduces itself in a positively entropic universe. Competition and selection become the inescapable consequence of any expanding population constrained to a finite arena. Evolution is then the result of these fundamental interacting stochastic processes as they act on populations, generation after generation [11], [12]. The impact of evolutionary thinking on biology cannot be understated: "Nothing in biology makes sense except in the light of evolution" [13, frontispiece].
     Evolutionary thought, however, extends beyond the study of life. Evolution is an optimization process that can be simulated using a computer or other device and put to good engineering purpose. The interest in such simulations has increased dramatically in recent years as applications of this technology have been developed to supplant conventional technologies in power systems, pattern recognition, control systems, factory scheduling, pharmaceutical design, and diverse other areas.
     There are three broadly similar avenues of investigation in simulated evolution: evolution strategies, evolutionary programming, and genetic algorithms (with related efforts in genetic programming and classifier systems). When applied for practical problem solving, each begins with a population of contending trial solutions brought to the task at hand. New solutions are created by randomly altering the existing solutions. An objective measure of performance is used to assess the "fitness" or "error" of each trial solution, and a selection mechanism determines which solutions should be maintained as "parents" for the subsequent generation. The differences between the procedures are characterized by the types of alterations that are imposed on solutions to create offspring, the methods employed for selecting new parents, and the data structures that are used to represent solutions. But these differences are minor in comparison to the similarities in approach.
     Evolutionary computation has become the standard term that encompasses all of these techniques. The term is still relatively new and represents an effort to bring together researchers who have been working in these and other closely related fields but following different paradigms.
     This Transactions will serve as an archival repository for significant work in evolutionary computation. The scope is intentionally broad; although the primary focus is on the practical application of evolutionary algorithms, a rigorous theoretical understanding of the algorithms that are employed must also be given suitable attention. Other research in the areas of cultural algorithms, artificial life, molecular computing, evolvable hardware, and the use of simulated evolution to gain a better understanding of naturally evolved systems are also encouraged. This Transactions must be free to evolve with the community it serves.
     I would like to thank Walter Karplus, Charlie Robinson, Bob Marks, Russ Eberhart, Jim Bezdek, and Pat Simpson for their personal encouragement to start this Transactions. Special thanks are also owed to the IEEE staff, the Neural Networks Council, and the Evolutionary Computation Technical Committee, in particular Zbyszek Michalewicz, Thomas Baeck, and Pete Angeline, for their advice and assistance. Finally, I would like to express my appreciation to all of the Associate Editors who are volunteering their time and effort in support of this new publication. I trust that our efforts together will serve the evolutionary computation community well into the years to come.
 
David B. Fogel, Editor-in-Chief
Natural Selection, Inc.
La Jolla, CA 92037 USA

References
[1] R.A. Fisher, The Genetical Theory of Natural Selection. Oxford, UK: Clarendon, 1970.
 
[2] S. Wright, "The roles of mutation, inbreeding, crossbreeding, and selection in evolution," in Proc. 6th Int. Congr. Genetics, Ithaca, NY, vol. 1, pp. 356-366.
 
[3] J.B.S. Haldane, The Causes of Evolution. London: Longman, 1932.
 
[4] T. Dobzhansky, Genetics and the Origin of Species. New York: Columbia Univ. Press, 1937.
 
[5] J.S. Huxley, Evolution: The Modern Synthesis. London: Allen and Unwin, 1942.
 
[6] E. Mayr, Systematics and the Origin of Species. New York: Columbia Univ. Press., 1942.
 
[7] G.G. Simpson, Tempo and Mode in Evolution. New York: Columbia Univ. Press, 1944.
 
[8] B. Rensch, Neuere Probleme der Abstammungslehre. Stuttgart, Germany: Ferdinand Enke, 1947.
 
[9] G.L. Stebbins, Variation and Evolution in Plants. New York: Columbia Univ. Press, 1950.
 
[10] A. Hoffman, Arguments on Evolution: A Paleontologist's Perspective. New York: Oxford Univ. Press, 1989.
 
[11] J. Huxley, "The evolutionary process," in Evolution as a Process, J. Huxley, A.C. Hardy, and E.B. Ford, Eds. New York: Collier, 1963, pp. 9-33.
 
[12] D.E. Wooldridge, The Mechanical Man: The Physical Basis of Intelligence Life. New York: McGraw-Hill, 1968.
 
[13] T. Dobzhansky, F.J. Ayala, G.L. Stebbins, and J.W. Valentine, Evolution. San Francisco, CA: W.H. Freeman, 1977.

Biographical Sketch
David B. Fogel received the Ph.D. degree in engineering sciences (systems science) from the University of California at San Diego (UCSD) in 1992.
     He was a systems analyst at Titan Systems, Inc. (1984-1988), a senior principal engineer at ORINCON Corporation (1988-1993), and is now executive vice president and chief scientist of Natural Selection, Inc., since 1993. Dr. Fogel has published over 100 papers on evolutionary computation in journals and conferences, and is the author of two books, most recently Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, 1995. He serves as the editor-in-chief of the IEEE Transactions on Evolutionary Computation.
     Dr. Fogel is Co-Editor-in-Chief of the Handbook of Evolutionary Computation (Oxford, 1997), Associate Editor of BioSystems and the IEEE Transactions on Neural Networks, and is a member of the editorial boards of Evolutionary Computation, Fuzzy Sets & Systems, and Intelligence. He was the Technical Program Chairman for the 1995 IEEE International Conference on Evolutionary Computation (Perth, Australia) and is Program Chairman for the 1998 IEEE International Conference on Evolutionary Computation to be held as part of the World Congress on Computational Intelligence, Anchorage, AK, May, 1998. Dr. Fogel was the Founding President of the Evolutionary Programming Society (1991) and has served on numerous program committees of conferences in the area of evolutionary computation. He is a member of many technical societies including the American Association for Artificial Intelligence, the Evolutionary Programming Society, Sigma Xi, the American Association for the Advancement of Science, the New York Academy of Sciences, and the IEEE. He is also an associate member of the Center for the Study of Evolution and the Origin of Life (CSEOL) at UCLA.