.

0 (hodnocen0 x )

BK

Third edition

Global edition

Boston : Pearson, [2016]

xviii, 1132 stran : ilustrace ; 26 cm

ISBN 978-1-292-15396-4 (brožováno)

Always learning

Obsahuje bibliografii na stranách 1063-1093, bibliografické odkazy a rejstřík

001484507

Contents // I Artificial Intelligence // 1 Introduction 1 // 1.1 WhallsAI?... 1 // 1.2 The Foundations of Artificial Intelligence... 5 // 1.3 The History of Artificial Intelligence... 16 // 1.4 The State of the Alt... 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 // 11 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 Uninfonned 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 Propositional Logic: A Very Simple Logic... 243 // 7.5 Propositional Theorem Proving... 249 // 7.6 Effective Propositional Model Checking... 259 // 7.7 Agents Based on Propositional 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 Propositional 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 Infonnation ... 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 ... 748 // 18.11 Practical Machine Learning... 753 // 18.12 Summary. Bibliographical and Historical Notes, Exercises... 757 // 19 Knowledge in Learning 768 // 19.1 A Logical Formulation of Learning... 768 // Contents xv" // 19.2 Knowledge in Learning... Ill // 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 // xvjjj 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...W06 // 25.9 Summary. Bibliographical

and Historical Notes, Exercises... 1010 // VII Conclusions // 26 Philosophical Foundations 1 20 // 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 Al: The Present and Future ?44 // 27.1 Agent Components ... ?44 // 27.2 Agent Architectures... ?47 // 27.3 Are We Going in the Right Direction? ... 1049 // 27.4 What If Al Does Succeed? ... ?51 // A Mathematical background 1053 // A. 1 Complexity Analysis and 0() Notation... 1053 // A.2 Vectors. Matrices, and Linear Algebra ... 1055 // A. 3 Probability Distributions...?57 // ? Notes on Languages and Algorithms 1060 // B. 1 Defining Languages with Backus-Naur Form (BNF)... 1060 // B.2 Describing Algorithms w’ith Pseudocode...1061 // B.3 Online Help...10? // Bibliography 1063 // Index // 1095