Artificial Intelligence: A Modern Approach (4 Ed. Global Ed.) | 誠品線上

Artificial Intelligence: A Modern Approach (4 Ed. Global Ed.)

內容簡介

內容簡介 The most comprehensive, up-to-date introduction to the theory and practice of artificial intelligenceThe long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.I Artificial Intelligence 1 Introduction 2 Intelligent Agents II Problem-solving 3 Solving Problems by Searching 4 Search in Complex Environments 5 Constraint Satisfaction Problems 6 Adversarial Search and Games III Knowledge, reasoning, and planning 7 Logical Agents 8 First-Order Logic 9 Inference in First-Order Logic 10 Knowledge Representation 11 Automated Planning IV Uncertain knowledge and reasoning 12 Quantifying Uncertainty 13 Probabilistic Reasoning 14 Probabilistic Reasoning over Time 15 Making Simple Decisions 16 Making Complex Decisions 17 Multiagent Decision Making 18 Probabilistic ProgrammingV Machine Learning 19 Learning from Examples 20 Knowledge in Learning 21 Learning Probabilistic Models 22 Deep Learning 23 Reinforcement Learning VI Communicating, perceiving, and acting 24 Natural Language Processing 25 Deep Learning for Natural Language Processing 26 Robotics 27 Computer Vision VII Conclusions 28 Philosophy, Ethics, and Safety of AI 29 The Future of AI Appendix A: Mathematical Background Appendix B: Notes on Languages and Algorithms Bibliography Index

作者介紹

作者介紹 RUSSELL、NORVIGStuart Russell：加州大學柏克萊分校計算機科學教授、加州大學舊金山分校神經外科兼任教授Peter Norvig：現為Google公司研究總監

產品目錄

產品目錄 I Artificial Intelligence 1 Introduction 2 Intelligent Agents II Problem-solving 3 Solving Problems by Searching 4 Search in Complex Environments 5 Constraint Satisfaction Problems 6 Adversarial Search and Games III Knowledge, reasoning, and planning 7 Logical Agents 8 First-Order Logic 9 Inference in First-Order Logic 10 Knowledge Representation 11 Automated Planning IV Uncertain knowledge and reasoning 12 Quantifying Uncertainty 13 Probabilistic Reasoning 14 Probabilistic Reasoning over Time 15 Making Simple Decisions 16 Making Complex Decisions 17 Multiagent Decision Making 18 Probabilistic ProgrammingV Machine Learning 19 Learning from Examples 20 Knowledge in Learning 21 Learning Probabilistic Models 22 Deep Learning 23 Reinforcement Learning VI Communicating, perceiving, and acting 24 Natural Language Processing 25 Deep Learning for Natural Language Processing 26 Robotics 27 Computer Vision VII Conclusions 28 Philosophy, Ethics, and Safety of AI 29 The Future of AI Appendix A: Mathematical Background Appendix B: Notes on Languages and Algorithms Bibliography Index

商品規格

最佳賣點

最佳賣點 : ‧ NEW - New sections on Monte Carlo search for games and robotics.
‧ NEW - New sections on privacy, fairness, the future of work, and safe AI.