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Blondie24: Playing at the Edge of AI ペーパーバック – イラスト付き, 2001/9/22
購入オプションとあわせ買い
- 本の長さ424ページ
- 言語英語
- 出版社Morgan Kaufmann
- 発売日2001/9/22
- 寸法13.97 x 2.44 x 17.78 cm
- ISBN-101558607838
- ISBN-13978-1558607835
商品の説明
出版社からのコメント
Here's the story of a computer that taught itself to play checkers far better than its creators ever could. Blondie24 uses a program that emulates the basic principles of Darwin evolution to discover on its own how to excel at the game. Through this entertaining story, the book provides the reader some of the history of AI and explores its future.
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 other games played by human grand masters, or databases of moves for the endgame. It created its own means for evaluating the patterns of pieces that it experienced by evolving artificial neural networks--mathematical models that loosely describe how a brain works.
As we remember Arthur C. Clarke's prediction of the successful creation of machines that think like humans, David Fogel dramatically demonstrates how evolutionary computation may in fact bring us to our goal of creating a thinking machine far more quickly than traditional artificial intelligence has been able to do.
レビュー
著者について
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.
登録情報
- 出版社 : Morgan Kaufmann; 第1版 (2001/9/22)
- 発売日 : 2001/9/22
- 言語 : 英語
- ペーパーバック : 424ページ
- ISBN-10 : 1558607838
- ISBN-13 : 978-1558607835
- 寸法 : 13.97 x 2.44 x 17.78 cm
- カスタマーレビュー:
著者について
著者の本をもっと発見したり、よく似た著者を見つけたり、著者のブログを読んだりしましょう
他の国からのトップレビュー
Deep Blue beat Gary Kasparov but only after a multi-year effort involving special hardware and was a program that was specifically designed to play chess.
Blondie24 'evolved itself' using non-special hardware (Pentium 400MHz) and in a matter of months beats 99% of all human players - WITHOUT KNOWING ANYTHING ABOUT DRAUGHTS.
Part 1 of the book is an overview of the two philosophies of AI embedded in Deep Blue and Blondie24 respectively. The argument is well made that Hal2001 could never be programmed in a conventional fashion.
Part 2 is the story of Blondie's creation - if anything here the most impressive item is the author's enthusiasm which is contagious.
Three qualifications:
1) on a technical quibble front Blondie24 is actually a co-evolved board valuation function which can only play draughts as it is embedded in a conventionally programmed mini-maxing game playing program. However one can hardly quibble with an author who includes an appendix of criticisms of his contentions!
2) at a more fundamental level Blondie24 is not a learning program (as far as I can see it learns nothing from its games) but rather the output of a learning system. This may be an interesting area for future study as, having evolved a 'good solution' it seems a pity to then 'waste' its future experiences.
3) like most highly skilled people Fogel makes it look easier than it is. If, sucked in by enthusiasm, one is tempted to try for oneself such an approach one finds a great number of pitfalls - it ain't as easy as he makes it look :-)
Overall no hesitation in suggesting that you buy this book if you have a lively, wide-ranging mind. If you liked reading about any of Chaos, Complexity, ALife etc as new paradigms then you have to buy this one.
MRB
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.
For the beginner this book offers a nice intuitive introduction to subject areas such as neural nets and genetic algorithms.
The expert is not likely to learn any technical matertial but will probably enjoy it as it is a wonderfully written story and perhaps some inspiration. If all you want is a technical manual, then you should look elsewhere.
My level of knowledge of AI is closer to a beginner than an expert. Here are three things that struck me:
1. How long it can take to evolve a good solution. One example from the book took 6 months using pentium 400.
2. How petty academics can be. The last section contains comments made by referees reviewing papers written by the author in scientific journals. Most of them smack of "Damn why didn't I think of that. Well since I didn't, I will try to block someone who did".
3. How elegant GA can be. This book has inspired me to seriously study the various techniques in evolutionary methods.
There are two minor annoyances I found in the book. They are both related to the layout of the book. The book is almost square and has relatively short sides. I assume this was done to make the book look like a checkerboard. This gives the book an odd "feel". Because of the dimentions, the amount of material on each page is relatively small and often the diagrams are not on the same page as the words describing them. However these are very minor complaints on what is a very fine book.
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.