San Francisco, CA USA : Morgan Kaufmann Publishers, 2002.
Book — 404 p. : ill. ; 18 cm.
Part 1 - Setting the Stage
Chapter 1 - Intelligent Machines: Imitating Life
Chapter 2 - Deep Blue: A Triumph of AI?
Chapter 3 - Building An Artificial Brain
Chapter 4 - Evolutionary Computation: Putting Nature to Work
Chapter 5 - Blue Hawaii: Natural Selection
Chapter 6 - Checkers
Chapter 7 - Chinook: The Man-machine Checkers Champion
Chapter 8 - Samuel's Learning Machine
Chapter 9 - The Samuel-Newell Challenge
Part 2 - The Making of Blondie
Chapter 10 - Evolving in the Checkers Environment
Chapter 11 - In The Zone
Chapter 12 - A Repeat Performance
Chapter 13 - A New Dimension
Chapter 14 - Letting the Genie Out of the Bottle
Chapter 15 - Blondie24 Epilogue: The Future of Artificial Intelligence Appendix: Your Honor, I Object! Notes Index About the Author.
(source: Nielsen Book Data)
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. (source: Nielsen Book Data)