- Series: The Morgan Kaufmann Series in Artificial Intelligence
- Paperback: 406 pages
- Publisher: Morgan Kaufmann; 1 edition (October 10, 2001)
- Language: English
- ISBN-10: 1558607838
- ISBN-13: 978-1558607835
- Product Dimensions: 5.5 x 1 x 7 inches
- Shipping Weight: 1.2 pounds (View shipping rates and policies)
- Average Customer Review: 42 customer reviews
- Amazon Best Sellers Rank: #1,142,958 in Books (See Top 100 in Books)
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Blondie24: Playing at the Edge of AI (The Morgan Kaufmann Series in Artificial Intelligence) 1st Edition
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"Enlightenment Now: The Case for Reason, Science, Humanism, and Progress"
Is the world really falling apart? Is the ideal of progress obsolete? Cognitive scientist and public intellectual Steven Pinker urges us to step back from the gory headlines and prophecies of doom, and instead, follow the data: In seventy-five jaw-dropping graphs, Pinker shows that life, health, prosperity, safety, peace, knowledge, and happiness are on the rise. Learn more
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What must it do to the human male ego to find out that the young woman who just handily won an online game of checkers is actually a sleek piece of software with no real understanding of the game's rules? Evolutionary programmers David B. Fogel and Kumar Chellapilla learned this and many other lessons in their quest to build a problem-solver divorced from human expertise. Fogel's book Blondie24: Playing at the Edge of AI captures their spirit of good-natured questioning of the received wisdom of traditional checkers playing and AI research.
The writing is surprisingly engaging, coming from a software researcher; even readers with little interest in checkers will follow Fogel's many game analyses with rising interest as his neural networks increase in prowess. Ever the scientist, he includes a laundry list of fairly harsh critiques of his work--with rebuttals--as an appendix. Devotees of cutting-edge AI, online psychology, or tournament-level checkers will find plenty of interest in the exploits of Blondie24. --Rob Lightner
"Meet Blondie. She's a 24-year old graduate student in mathematics at the University of California at San Diego. She skis and surfs, and is an ace at math. But her real claim to fame is her amazing ability to play checkers. She's really good--not good enough to defeat a grand master, but she did earn a spot in the top 500 of an international checkers tournament. Considering that she taught herself how to play without reading books, taking classes, or getting tips from experienced players--that's impressive. And considering that Blondie is only a computer program, and the rest of her persona is just a product my imagination, you might say that's really impressive!"-from the Introduction
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The author's main thesis is the value of using concepts of evolutionary programming to bring about the rise of intelligent machines. The author clearly believes that before "HAL-like" machines can be built, researchers must construct computer programs that can teach themselves how to solve problems without any help. Intelligent machines must be creative, and learn and adapt to new circumstances. Traditional research in artificial intelligence has been geared towards building machines that emulate human intelligence, and this will not do in the author's view. The research did not address the true definition and meaning of intelligence, but instead made the goal of creating machines that think and act like humans, whence the famous "Turing test" for machine intelligence. The author completely rejects this test and holds it responsible for bringing about the "AI winter" where no substantive progress was made. "The key to creating truly creative computers", he says, "lies in mimicking nature's process of evolution."
The author though was not comfortable with merely refuting arguments about the Turing test or other strategies for designing intelligent machines. He knows that such argument-counterargument activity will not result in sound approaches to artificial intelligence. Therefore, he sought to construct a working, viable alternative, which produces results that can be checked. Intelligence for the author is based on decision making, such as how to obtain resources, and how to respond to environmental changes by prioritizing goals. "Intelligence is the property that allows living organisms to sense, react to, and learn from their environment in order to adapt their behavior to better promote their survival", he says.
Hence, the author brings in the evolutionary paradigm to artificial intelligence, and to give credence to his view, he attempts to create a program that will learn the game of checkers and then play it well, at least from the standpoint of the checkers game rating system. The book is a very detailed overview of how he and his collaborators went about doing this, the most interesting strategy being the use of neural networks, the topology of which is not set beforehand, but is evolved according to a "survival of the fittest" process. The author, through diagrams, gives the reader a taste of the moves that were made as the program dealt with online checkers games.
The author even gives a dose of the criticism he received from referees when his results were submitted to professional journals, and this gives the book greater appeal from the standpoint of intellectual honesty. Certainly the author and those he worked with have achieved a great deal in the context of building intelligent machines. It remains to be seen whether evolutionary programming can be extended to situations that require even more creativity, such as that of generating new and interesting results in pure mathematics. This is the ultimate test in my view of machine intelligence. It is not immediately obvious how this is to be done in the evolutionary programming or indeed of any other paradigm in artificial intelligence.
The first half is quite good, giving very basic background information on neural networks and machine learning algorithms as well as a brief history of the two best known checkers programs, Samuels' machine learning checkers player and Chinook, the best ever player (so far).
It's the second half of the book, however, that kicks the story into overdrive. Fogel begins describing how he and his partner, Kumar Chellapilla, made their design decisions, evolved a neural net, then began playing it against humans over the internet. Even if you aren't all that interested in checkers (I am not) the games as they are described by Fogel become at least as interesting as any close sporting event, especially in those cases where the neural net set up traps for its opponents that neither Fogel nor the other player could foresee. There were times that I couldn't stop reading. I'd get off the bus to work, get in the office, and continue until I could pull myself away. The second half of this book is as much a page turner as the best novels I've read.
An absolute must read for anyone interested in where AI needs to go.
David Fogel is a world renowned expert and innovator in the development of evolutionary learning techniques described in Blondie24. His work is the state of the art, well known and respected by all in the field. The program and its implications are not only fascinating but extremely important and I believe a real look into the future for the development of `intelligent' systems.
I highly recommend Blondie24 to anyone even mildly interested in current AI technologies and the future of computing and intelligent systems. It's a great book.