John Holland is a pioneer in computer science whose work has been widely used in fields ranging from economics and psychology to computer design.
Holland created the genetic algorithm, a general computational algorithm used to improve problem solving by recombining and mutating previous solutions. His investigations of learning systems led to his creation of classifier systems, which are sets of interacting condition/action rules. With the tool of classifier systems, he solved two practical problems in artificial intelligence: how to design procedures that can learn appropriate behavior rather than have the behavior programmed in, and how to test new behaviors while avoiding system breakdown. He is currently studying complex adaptive systems composed of interacting adaptive agents such as ecosystems, economies, and immune systems. Holland is the author of a number of books, including Hidden Order: How Adaptation Builds Complexity (1995) and Emergence: From Chaos to Order (1998).
Holland is a professor of psychology and of computer science and engineering at the University of Michigan, where he has been on the faculty since 1959. He also serves as an external professor at the Santa Fe Institute.
Holland received a B.S. (1950) from the Massachusetts Institute of Technology, and an M.A. (1954) and a Ph.D. (1959) from the University of Michigan.