Artificial Intelligence - Stuart Russell

Artificial Intelligence

Stuart Russell

出版社

Pearson

出版时间

2009-12-11

ISBN

9780136042594

评分

★★★★★
书籍介绍

The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.

Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor of computer science, director of the Center for Intelligent Systems, and holder of...

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AI导读
核心看点
  • 全球1500多所高校采用的AI权威教材
  • 系统涵盖搜索、逻辑、概率与学习等核心
  • 从智能体视角构建完整的人工智能知识体系
适合谁读
  • 计算机专业本科生及研究生
  • 人工智能领域的从业者与研究者
  • 希望系统掌握AI理论基础的爱好者
读前提醒
  • 内容大而全,适合查阅概念而非深究细节
  • 前半部分难度较大,后半部分相对容易理解
  • 建议搭配官方代码库学习以辅助理解算法
读者共识
  • 公认的人工智能领域标准教科书与经典巨著
  • 内容全面但部分章节略显冗长,排版待优化
  • 中文译本质量参差不齐,强烈建议阅读原版

本导读基于书籍简介、目录、原文摘录、短评和书评生成,不等同于全文精读。

精彩摘录
  • "不记得历史的算法注定要重复历史。 有3种方法可以解决这一问题。 第一,我们可以记住之前到达的所有状态(就像最佳优先搜索一样),这样能够检测到所有冗余路径,并只保留每个状态的最优路径。这适用于存在大量冗余路径的状态空间,当内存可以容纳下已达状态表时,它是首选方法。 第二,我们不必担心对过去的重复。在一些问题形式化中,很少或不可能出现两条路径到达相同状态。以装配问题为例,每个动作都会将一个零件添加到一个不断发展的装配中,零件是有序的,因此可以先添加A,然后再添加B,但不能先添加B,然后再添加A。对于这些问题, 如果我们不记录已达状态也不检查冗余路径,则可以节省内存空间。如果搜索算法会检查冗余路径,"
  • "We can evaluate an algorithm's performance in four ways: Completeness: Is the algorithm guaranteed to find a solution when there is one? Optimality: Does the strategy find the optimal solution? Time complexity: How long does it take to find a solution? Space complexity: How much memory is needed to "
  • "斯图尔特•罗素教授和彼得•诺维格博士的《人工智能:现代方法》一书,是美国最为经典、最具权威性的大学教科书。 说它经典,是因为这本书长期以来都是美国大部分知名大学人工智能课程的教科书,今天也已经被全世界1500多所大学采用为教材,其内容覆盖了到每一版出版时为止世界人工智能的主流技术和方法。说它权威,是因为这本书是几乎所有人工智能从业者的参考书,但凡人们对某些人工智能的概念发生争议时,就会以这本书的讲述为准。 2002年,我有幸成为诺维格博士的下属,先后在谷歌公司的搜索部门以及研究部门从事与机器学习相关的工作。 诺维格博士是作为人工智能专家和科技管理者,被谷歌公司请来负责研发工作的。在我和他共事的"
  • "AI currently encompasses a huge variety of subfields, ranging from the general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on a crowded street, and diagnosing diseases. AI is relevant to any intellectual task; it is t"
  • "The Turing Test, proposed by Alan Turing (1950), was designed to provide a satisfactory operational definition of intelligence. A computer passes the test if a human interrogator, after posing some written questions, cannot tell whether the written responses come from a person or from a computer."
  • "•natural language processing to enable it to communicate successfully in English; •knowledge representation to store what it knows or hears; •automated reasoning to use the stored information to answer questions and to draw new conclusions; •machine learning to adapt to new circumstances and to dete"
  • "Aristotle (384-322 B.C.), whose bust appears on the front cover of this book, was the first to formulate a precise set of laws governing the rational part of the mind. He developed an informal system of syllogisms for proper reasoning, which in principle allowed one to generate conclusions mechanica"
  • "Notice that we said environment states, not agent states. if we define success in terms of agent's opinion of its own performance, an agent could achieve perfect rationality simply by deluding itself that its performance was perfect. Human agents in particular are notorious for "sour grapes"—believi"
作者简介
Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor of computer science, director of the Center for Intelligent Systems, and holder of the Smith–Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was cowinner of the Computers and Thought Award. He was a 1996 Miller Professor of the University of California and was appointed to a Chancellor’s Professorship in 2000. In 1998, he gave the Forsythe Memorial Lectures at Stanford University. He is a Fellow and former Executive Council member of the American Association for Artificial Intelligence. He has published over 100 papers on a wide range of topics in artificial intelligence. His other books include The Use of Knowledge in Analogy and Induction and (with Eric Wefald) Do the Right Thing: Studies in Limited Rationality. Peter Norvig is currently Director of Research at Google, Inc., and was the director responsible for the core Web search algorithms from 2002 to 2005. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Previously, he was head of the Computational Sciences Division at NASA Ames Research Center, where he oversaw NASA’s research and development in artificial intelligence and robotics, and chief scientist at Junglee, where he helped develop one of the first Internet information extraction services. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He received the Distinguished Alumni and Engineering Innovation awards from Berkeley and the Exceptional Achievement Medal from NASA. He has been a professor at the University of Southern California and a research faculty member at Berkeley. His other books are Paradigms of AI Programming: Case Studies in Common Lisp and Verbmobil: A Translation System for Face-to-Face Dialog and Intelligent Help Systems for UNIX.
目录
Part I: Artificial Intelligence
Chapter 1: Introduction ... 1
1.1. What Is AI? ... 1
1.1.1. Acting humanly: The Turing Test approach ... 2
1.1.2. Thinking humanly: The cognitive modeling approach ... 3

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用户评论
粗略翻了一下,其实我不是很喜欢这种大而全的书,但不得不说作者太nb了,基本啥都涉及到,而且都点到了重点,这本书真适合买来收藏
看了其中几章,很好玩,有机会再好好研读吧。
三主线,强化学习,图模型,神经网络
text book
上了半学期课了,然而Q小朋友刚得知cs188老师Russell就是这本书作者并且这本书也是我们的教材,Q同学表示自己不应当翘课,应当亲自去听课。。。还是他国内的朋友告诉他的。。。服了。。
全世界的人工智能导论课好像都在用这本书的体系来组织教学大纲......写的真啰嗦,一学期的课上完了也没觉得有任何收获......
AI不止是ML啊, game, logic, bayes, HMM, RL都有用武之处!可配合 https://inst.eecs.berkeley.edu/~cs188/sp22/ 学习
第一章和最后一章非常的philosophical,看完之后对人生有了新感悟
实在是太多了
教材
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