人工智能：一种现代的方法

I Artificial Intelligence 1 Introduction 2 IntelligentAgents 11 Problem-solving 3 Solving Problems by Searching 4 Informed Search and Exploration 5 Constraint Satisfaction Problems 6 Adversarial Search Ill Knowledge and reasoning 7 Logical Agents 8 First-Order Logic 9 Inference in First-Order Logic 10 Knowledge Representation IV Planning 11 Planning

I Artificial Intelligence 1 Introduction 2 IntelligentAgents 11 Problem-solving 3 Solving Problems by Searching 4 Informed Search and Exploration 5 Constraint Satisfaction Problems 6 Adversarial Search Ill Knowledge and reasoning 7 Logical Agents 8 First-Order Logic 9 Inference in First-Order Logic 10 Knowledge Representation IV Planning 11 Planning 12 Planning and Acting in the Real WOrldV Uncertain knowledge and reasoning 13 Uncertainty 14 Probabilistic Reasoning 15 Probabilistic Reasoning over Time 16 Making Simple Decisions 17 Making Complex DecisionsVI Learning 18 Learning from Observations 19 Knowledge in Learning 20 Statistical Learning Methods 21 Reinforcement Learning Vll Communicating, perceiving, and acting 22 Communication 23 Probabilistic Language Processing 24 Perception 25 RobottesVlll ConCluSionS 26 Philosophical Foundations 27 Al: Present and Future A Mathematical background B Notes on Languages and Algorithms.Bibliography Index

本书被全世界89个国家的900多所大学用作教材。 本书以详尽和丰富的资料，从理性智能体的角度，全面阐述了人工智能领域的核心内容，并深入介绍了各个主要的研究方向。全书分为8大部分：第一部分“人工智能”，第二部分“问题求解”，第三部分“知识与推理”，第四部分“规划”，第五部分“不确定知识与推理”，第六部分“学习”，第七部分“通信、感知与行动”，第八部分“结论”。本书既详细介绍了人工智能的基本概念、思想和算法，还描述了其各个研究方向最前沿的进展，同时收集整理了详实的历史文献与事件。另外，本书的配套网址http://aima.cs.berkeley.edu/为教师和学生提供了大量教学和学习资料。 本书适合于不同层次和领域的研究人员及学生，是高等院校本科生和研究生人工智能课的首选教材，也是相关领域的科研与工程技术人员的重要参考书。