Blondie24: Playing at the Edge of AI

Blondie24: Playing at the Edge of AI

by David B. Fogel

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Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by using a program that emulated the basic principles of Darwinian evolution—random variation and natural selection— to discover on its own how to excel at the game.

Unlike Deep Blue, the celebrated chess machine that beat Garry


Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by using a program that emulated the basic principles of Darwinian evolution—random variation and natural selection— to discover on its own how to excel at the game.

Unlike Deep Blue, the celebrated chess machine that beat Garry Kasparov, the former world champion chess player, this evolutionary program didn't have access to strategies employed by human grand masters, or to databases of moves for the endgame moves, or to other human expertise about the game of chekers. With only the most rudimentary information programmed into its "brain," Blondie24 (the program's Internet username) created its own means of evaluating the complex, changing patterns of pieces that make up a checkers game by evolving artificial neural networks—-mathematical models that loosely describe how a brain works.

It's fitting that Blondie24 should appear in 2001, the year when we remember Arthur C. Clarke's prediction that one day we would succeed in creating a thinking machine. In this compelling narrative, David Fogel, author and co-creator of Blondie24, describes in convincing detail how evolutionary computation may help to bring us closer to Clarke's vision of HAL. Along the way, he gives readers an inside look into the fascinating history of AI and poses provocative questions about its future.

• Brings one of the most exciting areas of AI research to life by following the story of Blondie24's development in the lab through her evolution into an expert-rated checkers player, based on her impressive success in Internet competition.
• Explains the foundations of evolutionary computation, simply and clearly.
• Presents complex material in an engaging style for readers with no background in computer science or artificial intelligence.
• Examines foundational issues surrounding the creation of a thinking machine.
• Debates whether the famous Turing Test really tests for intelligence.
• Challenges deeply entrenched myths about the successes and implication of some well-known AI experiments
• Shows Blondie's moves with checkerboard diagrams that readers can easily follow.

Editorial Reviews

From the Publisher
"Argues convincingly that the future of artificial intelligence lies . . . in programs that can automatically improve themselves over time—without the bias of human knowledge. . . . I wholeheartedly recommend it to the general public and AI experts alike." — Dr. Peter Stone, Artificial Intelligence Principles Research Department, AT&T Labs Research

"An absorbing and enchanting tale of a personal quest for the deeper meaning of AI." — Nicholas Gessler, Director, UCLA Center for Computational Social Science

"Leads us to question the accepted vision for attaining true AI." — Dr. Ian Watson, Department of Computer Science, University of Auckland

"David has written an important and influential book. Not only is the discussion of Blondie24, the cute checker playing heroine of the book, a lively romp through the ins and outs of evolutionary programming but it sets the stage for David's more serious and far reaching discussion of what is right and wrong in our quest for a companion intelligence". — Earl Cox, Vice President and Chief Scientist, Panacya, Inc.

"Blondie24 is a fascinating and informative book that will be absolutely engrossing for anyone with an interest in artificial intelligence and computers. Although Master-level checkers programs have been around for a while, they have all used brute force to achieve their goals. The Blondie24 project represents the first serious attempt since Samuel's experiments in the 1950s to do something much more interesting and elegant: create a checkers program that can learn on its own. This book is easily accessible for the uninitiated, and I guarantee that you'll be swept along." — Gil Dodgen, author of the computer program, World Championship Checkers

"My AI students will love this engaging and instructive book, and it will fit perfectly into my HAL based course on AI Programming. This book will do much in establishing the connection between artificial evolution and artificial intelligence. The ice of the 'AI winter' is at last beginning to melt and it feels good!" — Dr. Julian Miller, School of Computer Science, University of Birmingham
The Barnes & Noble Review
Having lived through the actual time period imagined in Stanley Kubrick's classic film 2001, one can't help asking: Will we ever create an intelligent machine like the unforgettable HAL -- one that's flexible enough to adapt its behavior to different environments, solving whatever problems come its way (though, ideally, not as neurotic)?

Moore's law is still working -- processors are doubling in speed every 18 months -- but, says, David Fogel, unless we fundamentally change our approach to artificial intelligence, we may never create HAL, or anything like him. Even Deep Blue, the IBM computer that outmaneuvered Garry Kasparov, is merely an incredibly fast calculator optimized for playing chess.

The alternative? It's straight outta Darwin: evolution. Stripped to its essence, evolution is "a never-ending two-step process of random variation and selection." Turns out you can write algorithms that do the same thing and begin building programs that actually do learn on their own, without being stuffed with knowledge ahead of time.

One of these "evolutionary algorithms," embedded in a program called "Blondie24," has learned how to play checkers well enough to win an online tournament. Blondie24's not at grandmaster level yet, but she's better than 99.61 percent of the 120,000 checkers players at Microsoft's

Not bad, when you consider that Fogel and his colleague Kumar Chellapilla told Blondie24 nothing about checkers except the barest rules. Not even the fact that people take turns when they're playing a board game, much less the importance of mobility, the value of kings, or the existence of obscure formations like the "Triangle of Oreo," All that she discovered on "her" own.

If Fogel and Chellapilla are right -- and increasing evidence says they are -- then Blondie24, their new book, may be remembered as a seminal text in the transformation of AI. Yesterday's sterile systems could only reprocess what they'd already been taught. Tomorrow's might learn just about anything on their own -- how to build molecules that never existed before or respond to the sudden appearance of, say, alien monoliths near the moons of Jupiter.

Blondie24 walks you through the entire project: the history of checkers-playing software, the design ideas that led to Blondie24, the tweaking that helped her deepen her skills (without proffering any unfair help), and the exhilaration that came at every milestone -- beating a master, winning a tournament, making an especially prescient move. You can feel the pride. And you can begin to see the future. (Bill Camarda)

Bill Camarda is a consultant, writer, and web/multimedia content developer with nearly 20 years' experience in helping technology companies deploy and market advanced software, computing, and networking products and services. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks For Dummies®, Second Edition.

This book explains how a computer, by replicating the processes of Darwinian evolution, taught itself to play checkers far better than its creators could have programmed it to play. Fogel (editor, ) considers the implications for evolutionary computations and artificial intelligence. Diagrams illustrate the evolutionary and computational processes at work, and the course of various games of checkers. Annotation c. Book News, Inc., Portland, OR (

Product Details

Elsevier Science
Publication date:
Morgan Kaufmann Series in Artificial Intelligence Series
Edition description:
New Edition
Product dimensions:
5.67(w) x 7.02(h) x 0.82(d)

Meet the Author

David B. Fogel is the CEO of Natural Selection, Inc., a company which addresses complex, real-world problems in the areas of industry, medicine, and defense by applying the techniques of evolutionary computation, neural networks, fuzzy systems, knowledge-based systems, and stochastic processes, among other technologies. Dr. Fogel was the founding president of the Evolutionary Programming Society and was elected a Fellow of the IEEE in 1999. He is the founding editor-in-chief of the IEEE Transactions on Evolutionary Computation and serves on the editorial boards of several journals including BioSystems, Fuzzy Sets and Systems, and Journal of Scheduling.

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