Artificial intelligence: a modern approach
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boston [und 24 weiteren]
Pearson
[2016]
|
| Ausgabe: | Third edition, global edition |
| Schriftenreihe: | Prentice Hall series in artificial intelligence
Always learning |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | "Authorized adaption from the United States edition, entitled 'Artificial intelligence: a modern approach', third edition, ISBN 9780136042594, by Stuart J. Russell and Peter Norvig published by Pearson Education © 2010." - Rückseite der Titelseite. - Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | xviii, 1132 Seiten Illustrationen, Diagramme |
| ISBN: | 9781292153964 1292153962 |
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Contents I Artificial Intelligence 1 Introduction 1.1 What Is AI?. 1.2 The Foundations of Artificial Intelligence. 1.3 The History of Artificial Intelligence. 1.4 The State of the Art. 1.5 Summary, Bibliographical and Historical Notes, Exercises. 1 1 5 16 28 29 2 Intelligent Agents 2.1 Agents and Environments . . . . 2.2 Good Behavior: The Concept of Rationality. 2.3 The Nature of Environments. 2.4 The Structure of Agents. 2.5 Summary, Bibliographical and Historical Notes, Exercises. 34 34 36 40 46 59 II Problem-solving 3 Solving Problems by Searching 3.1 Problem-Solving Agents. 3.2 Example Problems. 3.3 Searching for Solutions. 3.4 Uninformed Search Strategies. 3.5 Informed (Heuristic) Search Strategies. 3.6
Heuristic Functions . . . 3.7 Summary, Bibliographical and Historical Notes, Exercises. 64 64 69 75 81 92 102 108 4 Beyond Classical Search 4.1 Local Search Algorithms and Optimization Problems . 4.2 Local Search in Continuous Spaces. 4.3 Searching with Nondeterministic Actions. 4.4 Searching with Partial Observations. 4.5 Online Search Agents and Unknown Environments . 4.6 Summary, Bibliographical and Historical Notes, Exercises . . . . 120 120 129 133 138 147 153 5 Adversarial Search 5.1 Games. 5.2 Optimal Decisions in Games . 5.3 Alpha-Beta Pruning. . . 5.4 Imperfect Real-Time Decisions. 5.5 Stochastic Games. 161 161 163 167 171 177 xiii
xiv Contents 5.6 5.7 5.8 5.9 6 III Partially Observable Games. State-of-the-Art Game Programs. Alternative Approaches. Summary, Bibliographical and Historical Notes,Exercises. 180 185 187 189 Constraint Satisfaction Problems 6.1 Defining Constraint Satisfaction Problems. 6.2 Constraint Propagation: Inference in CSPs. 6.3 Backtracking Search for CSPs. 6.4 Local Search for CSPs. 6.5 The Structure of Problems . 6.6 Summary, Bibliographical and Historical Notes,Exercises. 202 202 208 214 220 222 227 Knowledge, reasoning, and planning 7 Logical Agents 7.1 Knowledge-Based Agents. 7.2 The Wumpus World . 7.3 Logic. 7.4 Propositional Logic: A Very Simple Logic. 7.5 Propositional Theorem
Proving. 7.6 Effective Propositional Model Checking. 7.7 Agents Based on Propositional Logic. 7.8 Summary, Bibliographical and Historical Notes,Exercises. 234 235 236 240 243 249 259 265 274 8 First-Order Logic 8.1 Representation Revisited . 8.2 Syntax and Semantics of First-Order Logic. 8.3 Using First-Order Logic . 8.4 Knowledge Engineering in First-Order Logic. 8.5 Summary, Bibliographical and Historical Notes,Exercises . . . 285 285 290 300 307 313 9 Inference in First-Order Logic 9.1 Propositional vs. First-Order Inference. 9.2 Unification and Lifting . . ------- . . . . 9.3 Forward Chaining . 9.4 Backward Chaining . 9.5 Resolution. 9.6 Summary, Bibliographical and Historical Notes,Exercises. 322 322 325 330 337 345 357 10 Classical Planning 10.1
Definition of Classical Planning. 10.2 Algorithms for Planning as State-Space Search. 10.3 Planning Graphs. 366 366 373 379
Contents XV 10.4 10.5 10.6 Other Classical Planning Approaches . . . . Analysis of Planning Approaches. Summary, Bibliographical and Historical Notes, Exercises. 387 392 393 11 Planning and Acting in the Real World 11.1 Time, Schedules, and Resources. 11.2 Hierarchical Planning. 11.3 Planning and Acting in Nondeterministic Domains. 11.4 Multiagent Planning. 11.5 Summary, Bibliographical and Historical Notes, Exercises. 401 401 406 415 425 430 12 Knowledge Representation 12.1 Ontological Engineering. 12.2 Categories and Objects . 12.3 Events. 12.4 Mental Events and Mental Objects. 12.5 Reasoning Systems for Categories . 12.6 Reasoning with Default Information . . . 12.7 The Internet Shopping World. 12.8 Summary,
Bibliographical and Historical Notes, Exercises. 437 437 440 446 450 453 458 462 467 IV Uncertain knowledge and reasoning 13 Quantifying Uncertainty 13.1 Acting under Uncertainty. 13.2 Basic Probability Notation. 13.3 Inference Using Full Joint Distributions. 13.4 Independence . 13.5 Bayes’ Rule and Its Use. 13.6 The Wumpus World Revisited. 13.7 Summary, Bibliographical and Historical Notes, Exercises . 480 480 483 490 494 495 499 503 14 Probabilistic Reasoning 14.1 Representing Knowledge in an Uncertain Domain. 14.2 The Semantics of Bayesian Networks. 14.3 Efficient Representation of Conditional Distributions. 14.4 Exact Inference in Bayesian Networks. 14.5 Approximate Inference in Bayesian Networks. 14.6 Relational and First-Order Probability Models. 14.7 Other Approaches to Uncertain
Reasoning. 14.8 Summary, Bibliographical and Historical Notes, Exercises. 510 510 513 518 522 530 539 546 551 15 Probabilistic Reasoning over Time 15.1 Time and Uncertainty. 566 566
Contents XVI 15.2 15.3 15.4 15.5 15.6 15.7 Inference in Temporal Models. Hidden Markov Models. Kalman Filters. Dynamic Bayesian Networks. Keeping Track of Many Objects. Summary, Bibliographical and HistoricalNotes, Exercises. 570 578 584 590 599 603 16 Making Simple Decisions 16.1 Combining Beliefs and Desires under Uncertainty. 16.2 The Basis of Utility Theory . . 16.3 Utility Functions. 16.4 Multiattribute Utility Functions. 16.5 Decision Networks . . .։. . 16.6 The Value of Information. 16.7 Decision-Theoretic Expert Systems. 16.8 Summary, Bibliographical and HistoricalNotes, Exercises. 610 610 611 615 622 626 628 633 636 17 Making Complex Decisions 17.1 Sequential
Decision Problems. 17.2 Value Iteration. 17.3 Policy Iteration. 17.4 Partially Observable MDPs. 17.5 Decisions with Multiple Agents: Game Theory. 17.6 Mechanism Design . 17.7 Summary, Bibliographical and HistoricalNotes, Exercises. 645 645 652 656 658 666 679 684 V Learning 18 Learning from Examples 18.1 Forms of Learning. 18.2 Supervised Learning. 18.3 Learning Decision Trees. 18.4 Evaluating and Choosing the Best Hypothesis . 18.5 The Theory of Learning . 18.6 Regression and Classification with Linear Models. 18.7 Artificial Neural Networks . 18.8 Nonparametric Models . 18.9 Support Vector
Machines. 18.10 Ensemble Learning . 18.11 Practical Machine Learning. 18.12 Summary, Bibliographical and HistoricalNotes, Exercises. 693 693 695 697 708 713 717 727 737 744 748 753 757 19 Knowledge in Learning 19.1 A Logical Formulation of Learning. 768 768
Contents xvii 19.2 19.3 19.4 19.5 19.6 Knowledge in Learning. . Explanation-Based Learning . Learning Using Relevance Information. Inductive Logic Programming. Summary, Bibliographical and Historical Notes,Exercises. 777 780 784 788 797 20 Learning Probabilistic Models 20.1 Statistical Learning . 20.2 Learning with Complete Data. 20.3 Learning with Hidden Variables: The EM Algorithm. 20.4 Summary, Bibliographical and Historical Notes,Exercises. 802 802 806 816 825 21 Reinforcement Learning 21.1 Introduction. 21.2 Passive Reinforcement Learning . 21.3 Active Reinforcement Learning. 21.4 Generalization in Reinforcement Learning . 21.5 Policy Search . 21.6 Applications of Reinforcement Learning. 21.7 Summary, Bibliographical
and Historical Notes,Exercises. 830 830 832 839 845 848 850 853 VI Communicating, perceiving, and acting 22 Natural Language Processing 22.1 Language Models. 22.2 Text Classification. 22.3 Information Retrieval. 22.4 Information Extraction. 22.5 Summary, Bibliographical and Historical Notes,Exercises. 860 860 865 867 873 882 23 Natural Language for Communication 23.1 Phrase Structure Grammars. 23.2 Syntactic Analysis (Parsing). 23.3 Augmented Grammars and Semantic Interpretation . 23.4 Machine Translation. 23.5 Speech Recognition. 23.6 Summary, Bibliographical and Historical Notes,Exercises. 888 888 892 897 907 912 918 24 Perception 24.1 Image Formation. 24.2 Early Image-Processing Operations. 24.3
Object Recognition by Appearance. 24.4 Reconstructing the 3D World. 24.5 Object Recognition from Structural Information. 928 929 935 942 947 957
xviii Contents 24.6 24.7 Using Vision. Summary, Bibliographical and HistoricalNotes,Exercises. 961 965 25 Robotics 971 25.1 Introduction. 971 25.2 Robot Hardware. 973 25.3 Robotic Perception. 978 25.4 Planning to Move. 986 25.5 Planning Uncertain Movements. 993 25.6 Moving. 997 25.7 Robotic Software Architectures. 1003 25.8 Application Domains.1006 25.9 Summary, Bibliographical and HistoricalNotes,Exercises. 1010 VII Conclusions 26 Philosophical Foundations 1020 26.1 Weak AI: Can Machines Act Intelligently?. 1020 26.2 Strong AI: Can Machines Really Think?.1026 26.3 The Ethics and Risks of Developing
ArtificialIntelligence. 1034 26.4 Summary, Bibliographical and HistoricalNotes,Exercises. 1040 27 AI: The Present and Future 1044 27.1 Agent Components .1044 27.2 Agent Architectures. 1047 27.3 Are We Going in the Right Direction? .1049 27.4 What If AI Does Succeed? . 1051 A Mathematical background 1053 A.l Complexity Analysis and 0() Notation. 1053 A.2 Vectors, Matrices, and Linear Algebra . 1055 A.3 Probability Distributions. 1057 В Notes B.l B.2 B.3 on Languages and Algorithms 1060 Defining Languages with Backus-Naur Form(BNF).1060 Describing Algorithms with Pseudocode. 1061 Online Help.1062 Bibliography 1063 Index 1095 |
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| spellingShingle | Russell, Stuart J. 1962- Norvig, Peter 1956- Artificial intelligence a modern approach Künstliche Intelligenz (DE-588)4033447-8 gnd |
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| title | Artificial intelligence a modern approach |
| title_auth | Artificial intelligence a modern approach |
| title_exact_search | Artificial intelligence a modern approach |
| title_full | Artificial intelligence a modern approach Stuart J. Russell and Peter Norvig ; contributing writers: Ernest Davis [und 7 weitere] |
| title_fullStr | Artificial intelligence a modern approach Stuart J. Russell and Peter Norvig ; contributing writers: Ernest Davis [und 7 weitere] |
| title_full_unstemmed | Artificial intelligence a modern approach Stuart J. Russell and Peter Norvig ; contributing writers: Ernest Davis [und 7 weitere] |
| title_short | Artificial intelligence |
| title_sort | artificial intelligence a modern approach |
| title_sub | a modern approach |
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THWS Schweinfurt Zentralbibliothek Lesesaal
| Signatur: |
2000 ST 300 R949(3) |
|---|---|
| Exemplar 1 | ausleihbar Verfügbar Bestellen |