Verfügbarkeit: Artificial intelligence | Technische Universität München

Artificial intelligence: a modern approach

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Bibliographische Detailangaben
Beteiligte Personen:	Russell, Stuart J. 1962- (VerfasserIn), Norvig, Peter 1956- (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	Boston [u.a.] Pearson 2010
Ausgabe:	3. ed., internat. ed.
Schriftenreihe:	Prentice Hall series in artificial intelligence
Schlagwörter:	Künstliche Intelligenz Aufgabensammlung Lehrbuch
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020426659&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	XVIII, 1132 S. Ill., graph. Darst.
ISBN:	9780132071482 0132071487

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adam_text	Contents I Artificial Intelligence 1 Introduction 1 1.1 What Is AI?................................. 1 1.2 The Foundations of Artificial Intelligence .................. 5 1.3 The History of Artificial Intelligence .................... 16 1.4 The State of the Art ............................. 28 1.5 Summary, Bibliographical and Historical Notes, Exercises ......... 29 2 Intelligent Agents 34 2.1 Agents and Environments .......................... 34 2.2 Good Behavior: The Concept of Rationality ................ 36 2.3 The Nature of Environments ......................... 40 2.4 The Structure of Agents ........................... 46 2.5 Summary, Bibliographical and Historical Notes, Exercises ......... 59 II Problem-solving 3 Solving Problems by Searching 64 3.1 Problem-Solving Agents ........................... 64 3.2 Example Problems .............................. 69 3.3 Searching for Solutions ........................... 75 3.4 Uninformed Search Strategies ........................ 81 3.5 Informed (Heuristic) Search Strategies ................... 92 3.6 Heuristic Functions ............................. 102 3.7 Summary, Bibliographical and Historical Notes, Exercises ......... 108 4 Beyond Classical Search 120 4.1 Local Search Algorithms and Optimization Problems ........... 120 4.2 Local Search in Continuous Spaces ..................... 129 4.3 Searching with Nondeterministic Actions .................. 133 4.4 Searching with Partial Observations ..................... 138 4.5 Online Search Agents and Unknown Environments ............ 147 4.6 Summary, Bibliographical and Historical Notes, Exercises ......... 153 5 Adversarial Search 161 5.1 Games .................................... 161 5.2 Optimal Decisions in Games ........................ 163 5.3 Alpha-Beta Pruning ............................. 167 5.4 Imperfect Real-Time Decisions ....................... 171 5.5 Stochastic Games .............................. 177 xiii xiv Contents 5.6 Partially Observable Games......................... 180 5.7 State-of-the-Art Game Programs ...................... 185 5.8 Alternative Approaches ........................... 187 5.9 Summary, Bibliographical and Historical Notes, Exercises ......... 189 6 Constraint Satisfaction Problems 202 6.1 Defining Constraint Satisfaction Problems ................. 202 6.2 Constraint Propagation: Inference in CSPs ................. 208 6.3 Backtracking Search for CSPs ........................ 214 6.4 Local Search for CSPs ............................ 220 6.5 The Structure of Problems .......................... 222 6.6 Summary, Bibliographical and Historical Notes, Exercises ......... 227 HI Knowledge, reasoning, and planning 7 Logical Agents 234 7.1 Knowledge-Based Agents .......................... 235 7.2 The Wumpus World ............................. 236 7.3 Logic ..................................... 240 7.4 Prepositional Logic: A Very Simple Logic ................. 243 7.5 Prepositional Theorem Proving ....................... 249 7.6 Effective Prepositional Model Checking .................. 259 7.7 Agents Based on Prepositional Logic ..................... 265 7.8 Summary, Bibliographical and Historical Notes, Exercises ......... 274 8 First-Order Logic 285 8.1 Representation Revisited .......................... 285 8.2 Syntax and Semantics of First-Order Logic ................. 290 8.3 Using First-Order Logic ........................... 300 8.4 Knowledge Engineering in First-Order Logic ................ 307 8.5 Summary, Bibliographical and Historical Notes, Exercises ......... 313 9 Inference in First-Order Logic 322 9.1 Prepositional vs. First-Order Inference ................... 322 9.2 Unification and Lifting ........................... 325 9.3 Forward Chaining .............................. 330 9.4 Backward Chaining ............................. 337 9.5 Resolution .................................. 345 9.6 Summary, Bibliographical and Historical Notes, Exercises ......... 357 10 Classical Planning 366 10.1 Definition of Classical Planning ....................... 366 10.2 Algorithms for Planning as State-Space Search ............... 373 10.3 Planning Graphs ............................... 379 Contents xv 10.4 Other Classical Planning Approaches .................... 387 10.5 Analysis of Planning Approaches ...................... 392 10.6 Summary, Bibliographical and Historical Notes, Exercises ......... 393 11 Planning and Acting in the Real World 401 11.1 Time, Schedules, and Resources ....................... 401 11.2 Hierarchical Planning ............................ 406 11.3 Planning and Acting in Nondeterministic Domains ............. 415 11.4 Multiagent Planning ............................. 425 11.5 Summary, Bibliographical and Historical Notes, Exercises ......... 430 12 Knowledge Representation 437 12.1 Ontological Engineering ........................... 437 12.2 Categories and Objects ........................... 440 12.3 Events .................................... 446 12.4 Mental Events and Mental Objects ..................... 450 12.5 Reasoning Systems for Categories ..................... 453 12.6 Reasoning with Default Information .................... 458 12.7 The Internet Shopping World ........................ 462 12.8 Summary, Bibliographical and Historical Notes, Exercises ......... 467 IV Uncertain knowledge and reasoning 13 Quantifying Uncertainty 480 13.1 Acting under Uncertainty .......................... 480 13.2 Basic Probability Notation .......................... 483 13.3 Inference Using Full Joint Distributions ................... 490 13.4 Independence ................................ 494 13.5 Bayes Rule and Its Use ........................... 495 13.6 The Wumpus World Revisited ........................ 499 13.7 Summary, Bibliographical and Historical Notes, Exercises ......... 503 14 Probabilistic Reasoning 510 14.1 Representing Knowledge in an Uncertain Domain ............. 510 14.2 The Semantics of Bayesian Networks .................... 513 14.3 Efficient Representation of Conditional Distributions ............ 518 14.4 Exact Inference in Bayesian Networks ................... 522 14.5 Approximate Inference in Bayesian Networks ............... 530 14.6 Relational and First-Order Probability Models ............... 539 14.7 Other Approaches to Uncertain Reasoning ................. 546 14.8 Summary, Bibliographical and Historical Notes, Exercises ......... 551 15 Probabilistic Reasoning over Time 566 15.1 Time and Uncertainty ............................ 566 xvi Contents 15.2 Inference in Temporal Models ........................ 570 15.3 Hidden Markov Models ........................... 578 15.4 Kalman Filters ................................ 584 15.5 Dynamic Bayesian Networks ........................ 590 15.6 Keeping Track of Many Objects ....................... 599 15.7 Summary, Bibliographical and Historical Notes, Exercises ......... 603 16 Making Simple Decisions 610 16.1 Combining Beliefs and Desires under Uncertainty ............. 610 16.2 The Basis of Utility Theory ......................... 611 16.3 Utility Functions ............................... 615 16.4 Multiattribute Utility Functions ....................... 622 16.5 Decision Networks .............................. 626 16.6 The Value of Information .......................... 628 16.7 Decision-Theoretic Expert Systems ..................... 633 16.8 Summary, Bibliographical and Historical Notes, Exercises ......... 636 17 Making Complex Decisions 645 17.1 Sequential Decision Problems ........................ 645 17.2 Value Iteration ................................ 652 17.3 Policy Iteration ................................ 656 17.4 Partially Observable MDPs ......................... 658 17.5 Decisions with Multiple Agents: Game Theory ............... 666 17.6 Mechanism Design ............................. 679 17.7 Summary, Bibliographical and Historical Notes, Exercises ......... 684 V Learning 18 Learning from Examples 693 18.1 Forms of Learning .............................. 693 18.2 Supervised Learning ............................. 695 18.3 Learning Decision Trees ........................... 697 18.4 Evaluating and Choosing the Best Hypothesis ............... 708 18.5 The Theory of Learning ........................... 713 18.6 Regression and Classification with Linear Models ............. 717 18.7 Artificial Neural Networks ......................... 727 18.8 Nonparametric Models ........................... 737 18.9 Support Vector Machines .......................... 744 18.10 Ensemble Learning ............................. 74g 18.11 Practical Machine Learning ......................... 753 18.12 Summary, Bibliographical and Historical Notes, Exercises ......... 757 19 Knowledge in Learning 75g 19.1 A Logical Formulation of Learning ................. 76g Contents xvii 19.2 Knowledge in Learning ........................... 777 19.3 Explanation-Based Learning ........................ 780 19.4 Learning Using Relevance Information ................... 784 19.5 Inductive Logic Programming ........................ 788 19.6 Summary, Bibliographical and Historical Notes, Exercises ......... 797 20 Learning Probabilistic Models 802 20.1 Statistical Learning ............................. 802 20.2 Learning with Complete Data ........................ 806 20.3 Learning with Hidden Variables: The EM Algorithm ............ 816 20.4 Summary, Bibliographical and Historical Notes, Exercises ......... 825 21 Reinforcement Learning 830 21.1 Introduction ................................. 830 21.2 Passive Reinforcement Learning ...................... 832 21.3 Active Reinforcement Learning ....................... 839 21.4 Generalization in Reinforcement Learning ................. 845 21.5 Policy Search ................................ 848 21.6 Applications of Reinforcement Learning .................. 850 21.7 Summary, Bibliographical and Historical Notes, Exercises ......... 853 VI Communicating, perceiving, and acting 22 Natural Language Processing 860 22.1 Language Models .............................. 860 22.2 Text Classification .............................. 865 22.3 Information Retrieval ............................ 867 22.4 Information Extraction ............................ 873 22.5 Summary, Bibliographical and Historical Notes, Exercises ......... 882 23 Natural Language for Communication 888 23.1 Phrase Structure Grammars ......................... 888 23.2 Syntactic Analysis (Parsing) ......................... 892 23.3 Augmented Grammars and Semantic Interpretation ............ 897 23.4 Machine Translation ............................. 907 23.5 Speech Recognition ............................. 912 23.6 Summary, Bibliographical and Historical Notes, Exercises ......... 918 24 Perception 928 24.1 Image Formation ............................... 929 24.2 Early Image-Processing Operations ..................... 935 24.3 Object Recognition by Appearance ..................... 942 24.4 Reconstructing the 3D World ........................ 947 24.5 Object Recognition from Structural Information .............. 957 xviii Contents 24.6 Using Vision ................................. 961 24.7 Summary, Bibliographical and Historical Notes, Exercises ......... 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 Historical Notes, 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 Artificial Intelligence ......... 1034 26.4 Summary, Bibliographical and Historical Notes, 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.I Complexity Analysis and O() Notation ................... 1053 A.2 Vectors, Matrices, and Linear Algebra ................... 1055 A.3 Probability Distributions ........................... 1057 В Notes on Languages and Algorithms 1060 B.I Defining Languages with Backus-Naur Form (BNF) ............ 1060 B.2 Describing Algorithms with Pseudocode .................. 1061 B.3 Online Help ................................. 1062 Bibliography 1063 Index 1095
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title	Artificial intelligence a modern approach
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title_full	Artificial intelligence a modern approach Stuart J. Russell and Peter Norvig
title_fullStr	Artificial intelligence a modern approach Stuart J. Russell and Peter Norvig
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Signatur:	0303 DAT 700f 2010 L 469(3) Lageplan
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Exemplar 2	Ausleihbar Am Standort
Exemplar 3	Ausleihbar Am Standort
Exemplar 4	Ausleihbar Am Standort
Exemplar 5	Ausleihbar Am Standort
Exemplar 6	Ausleihbar Am Standort
Exemplar 7	Ausleihbar Am Standort
Exemplar 8	Ausleihbar Am Standort
Exemplar 9	Ausleihbar Am Standort
Exemplar 10	Ausleihbar Am Standort
Exemplar 11	Ausleihbar Am Standort
Exemplar 12	Ausleihbar Am Standort
Exemplar 13	Ausleihbar Am Standort
Exemplar 14	Ausleihbar Am Standort
Exemplar 15	Ausleihbar Am Standort
Exemplar 16	Ausleihbar Am Standort
Exemplar 17	Ausleihbar Am Standort
Exemplar 18	Ausleihbar Am Standort