AI Application Programming (Programming Series) (英語) ペーパーバック – 2003/3/27
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Sortware engineer Jones demystifies techniques associated with artificial intelligence and shows how they can be useful in everyday applications. The book covers techniques including statistical algorithms, symbolic methods, evolutionary systems, and optimization methods. Each chapter covers the theory of the algorithm or technique under discussion
M. Tim Jones has been developing software since 1986. He has designed prototype AI systems using genetic algorithms for satellite attitude determination and mobile agents for distributed asset tracking. He has also published articles on embedded systems, network protocols, and AI for Dr. Dobb's Journal, Embedded Systems Programming, and Embedded Linux Journal. He currently works as a Senior Principal Software Engineer.
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The author explains and describes a number of algorithms and approaches to AI including classical path finding algorithms such as depth first search, breadth first search the A-star algorithm, as well as simulated annealing, the PSO algorithms (Particle Swarm Optimization), Adaptive Resonance Theory, what he calls classifier systems, and Ant Algorithms. He introduces Neural Networks focusing on feed-forward multilayer networks using back propagation learning. He also presents reinforcement learning and simple genetic algorithms. He discusses Artificial Life and Rules-based Systems and introduces fuzzy logic. There is a chapter on Natural Language Processing and another on Markov chains with the focus on the bigram model. Towards the end of the book there is a chapter on agent based systems applied to a web application. The book also has an introductory chapter on the history of AI and a concluding chapter on AI today.
One minor complaint I have is that topics such as classifiers (See5, quadratic, etc), robot path planning, adaptive control systems, robot systems emulating biological systems, are not mentioned. A few other minor complaints I have is that on page 210 he presents a formula (9.2) without defining the variables/symbols and the symbols in the equation make no sense in the context. Was that a “copy and paste” goof? Equation (4.2) on page 72 is cut in half and the equations toward the end of page 74 are obviously bogus. On page 96 his conclusions does not obviously follow from the discussion. In chapter ten he applies a genetic algorithm to a problem within evolutionary programming using a Virtual Machine, but without telling us what the problem actually is until much later, which makes it confusing. On page 176 he makes a claim I don’t believe.
Overall I recommend this book and I am glad I read it but I am not entirely enthusiastic about the book for reasons I’ve explained above.
Every chapter covers one kind of AI, one or two real-world applications and a list of other applications. There're more than enough illustrations for people like me who hate text-only book. A picture is worth a thousand words buddy. Here's my list of AI fields I remembered from the book: Genetic Algorithm, Neural Network, Ant, Particle Swarm, Simulated Annealing, ALife, Pathfinding, A-Star, ATR1, Classifier systems, Rule-based Aystems, Agent-based Software, NLP, Bigram, and Fuzzy Logic.
Examples are written in C language. Comments are plentiful. The codes, though short, pack a lot punches; a whole stack-only virtual machine (VM), for example, was written in less than 100 lines to illustrate how Genetic Algorithm works. Although I'm a VB.NET programmer, I could understand them quite easily.
I recommend this book to any programmer who like to get a big picture of artificial intelligence, who doesn't know where to begin or which algorithm is the right choice. This book should be the first-to-read but not the last, because it touches not far from the surface. I'd say this is the best precursor.
The code is fairly easy to read, and (to date) I have not found any errors in example code... but in terms of the actual 'writing', that's a whole different story. Formulas are missing halfs, inconsistencies in variable usage, it's seriously bad. Maybe I'm being a bit harsh, or maybe I got a bad edition (didn't buy from Amazon), but it looks exactly like the one listed (softcover, 2nd ed)..
If you're fairly proficient at C/C++ code, however, you should be able to follow the book ok... just expect to be reading more of the source code than the actual writing, half the time.
It was a required textbook for a class.
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