Artificial Intelligence IlluminatedJones & Bartlett Learning, 2004 - 739 Seiten Artificial Intelligence Illuminated presents an overview of the background and history of artificial intelligence, emphasizing its importance in today's society and potential for the future. The book covers a range of AI techniques, algorithms, and methodologies, including game playing, intelligent agents, machine learning, genetic algorithms, and Artificial Life. Material is presented in a lively and accessible manner and the author focuses on explaining how AI techniques relate to and are derived from natural systems, such as the human brain and evolution, and explaining how the artificial equivalents are used in the real world. Each chapter includes student exercises and review questions, and a detailed glossary at the end of the book defines important terms and concepts highlighted throughout the text. |
Im Buch
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... Identifying Optimal Paths 107 4.16.1 A * Algorithms 108 4.16.2 Uniform Cost Search 110 4.16.3 Greedy Search 111 4.16.4 Example : The Knapsack Problem 111 4.17 Chapter Summary 113 4.18 Review Questions 114 4.19 Exercises 115 4.20 Further ...
... Identifying Optimal Paths 107 4.16.1 A * Algorithms 108 4.16.2 Uniform Cost Search 110 4.16.3 Greedy Search 111 4.16.4 Example : The Knapsack Problem 111 4.17 Chapter Summary 113 4.18 Review Questions 114 4.19 Exercises 115 4.20 Further ...
Seite xxiv
... .6 Augmented Transition Networks 585 20.2.7 Chart Parsing 585 20.2.8 Semantic Analysis 588 20.2.9 Ambiguity and Pragmatic Analysis 589 20.3 Machine Translation 592 20.3.1 Language Identification 593 20.4 Information χχίν Contents.
... .6 Augmented Transition Networks 585 20.2.7 Chart Parsing 585 20.2.8 Semantic Analysis 588 20.2.9 Ambiguity and Pragmatic Analysis 589 20.3 Machine Translation 592 20.3.1 Language Identification 593 20.4 Information χχίν Contents.
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Ben Coppin. 20.3 Machine Translation 592 20.3.1 Language Identification 593 20.4 Information Retrieval 594 20.4.1 Stemming ... Identifying Textures 616 21.4.2 Structural Texture Analysis 620 21.4.3 Determining Shape and Orientation from ...
Ben Coppin. 20.3 Machine Translation 592 20.3.1 Language Identification 593 20.4 Information Retrieval 594 20.4.1 Stemming ... Identifying Textures 616 21.4.2 Structural Texture Analysis 620 21.4.3 Determining Shape and Orientation from ...
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Inhalt
Contents | 1 |
Uses and Limitations | 19 |
Knowledge Representation | 27 |
Search | 69 |
Advanced Search | 117 |
Game Playing | 143 |
Knowledge Representation and Automated | 173 |
Inference and Resolution for Problem Solving | 209 |
Genetic Algorithms | 387 |
Planning | 419 |
Planning Methods | 433 |
Advanced Topics | 463 |
Fuzzy Reasoning | 503 |
Intelligent Agents | 543 |
Understanding Language | 571 |
Machine Vision | 605 |
Rules and Expert Systems | 241 |
Machine Learning | 265 |
Neural Networks | 291 |
Probabilistic Reasoning and Bayesian Belief | 327 |
Learning through Emergent | 363 |
Glossary | 633 |
Bibliography | 697 |
719 | |
Häufige Begriffe und Wortgruppen
able actions agents alpha-beta pruning analysis applied architecture Artificial Intelligence Bayesian behavior block branching factor breadth-first search calculate Chapter chess chromosome classifier complex consider crossover current_node database decision tree defined depth-first search described determine edge edited examine example expert system Explain expression fact false frame fuzzy logic fuzzy sets game tree genetic algorithms goal node goal tree grammar Hence heuristic human hypothesis idea information retrieval input involves knowledge layer leaf nodes learning match means membership functions Minimax move MoveOnto natural language processing neural networks neurons nonmonotonic noun object operator optimal output path perceptron position possible Press probability PROLOG propositional logic queue reasoning represent representation robot root node rules schema search method search space search tree semantic sentence set of clauses shown in Figure simple situation solution Springer Verlag symbols techniques theorem tion training data true truth table variables vector words X₁