This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book.
目錄
1. Introduction.
2. Search.
3. Games.
4. Logic.
5. Planning.
6. Knowledge Representation.
7. Machine Learning.
8. Probabilistic Reasoning.
9. Stochastic Search.
10. Neural Networks.
11. Intelligent Agents.
12. Hybrid Models.
13. Languages of AI.
1. Introduction.
2. Search.
3. Games.
4. Logic.
5. Planning.
6. Knowledge Representation.
7. Machine Learning.
8. Probabilistic Reasoning.
9. Stochastic Search.
10. Neural Networks.
11. Intelligent Agents.
12. Hybrid Models.
13. Languages of AI.
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