Experiments in artificial intelligence have focused traditionally on replicating human behaviors in software. Although this approach has achieved some notable successes, including the Deep Blue chess machine that defeated Garry Kasparov in May, 1997, they are limited to addressing problems for which people already have the answers. An alternative approach, using computational intelligence methods such as evolutionary computing, can provide a computer with the ability to learn how to solve complex problems without relying on human expertise.
According to Fogel, what works best is the synergistic effect obtained by combining simulated evolutionary learning with human learning. As an example of this latter approach he tells the story of Blondie24, a checkers program supplied with only minimal information that was able to reach high levels of expertise thanks to the application of genetic algorithms. Fogel looks at other real-world applications in industry, medicine, and defense, as well as speculating on the future capabilities offered by these combined learning mechanisms.
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David B. Fogel is chief executive officer of Natural Selection, Inc. in La Jolla, CA. He received his Ph.D. in 1992 from the University of California at San Diego and is a Fellow of the IEEE. David served as the founding editor-in-chief of the IEEE Transactions on Evolutionary Computation between 1996 and 2002 and is currently editor-in-chief of BioSystems.
The author of over 200 publications in journals, conferences, and book chapters, David has also writen or co-written several books, including Blondie24: Playing at the Edge of AI, How to Solve It: Modern Heuristics, and Evolutionary Computation : Toward a New Philosophy of Machine Intelligence.
David co-founded Digenetics, Inc. - a sister-company to Natural Selection, Inc.- dedicated to promoting evolutionary computing for entertainment software. So far, the company has developed two games for checkers and chess that rely on evolutionary neural network technology.
This program is one of a series from the IT Conversations coverage of Accelerating Change 2005, held September 16-18, 2005 at Stanford University.
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