《人工智能:一种现代的方法(第3版)(影印版)》最权威、最经典的人工智能教材，已被全世界100多个国家的1200多所大学用作教材。《人工智能:一种现代的方法(第3版)(影印版)》的最新版全面而系统地介绍了人工智能的理论和实践，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。全书仍分为八大部分：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”。《人工智能:一种现代的方法(第3版)(影印版)》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，《人工智能:一种现代的方法(第3版)(影印版)》的配套网址为教师和学生提供了大量教学和学习资料。 《人工智能:一种现代的方法(第3版)(影印版)》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。

1997年5月11日，全世界数百万人通过电视观看了一场惊人的胜利——一台计算机战胜了欲捍卫世界冠军称号的卡斯帕罗夫，此举震惊了国际象棋界。 本书的作者许峰雄是“深蓝”的系统设计师，他避开难懂的术语，以非技术的谈话式的笔触，介绍了在“深蓝”与卡斯帕罗夫两次具有历史意义的弈战背后所发生的故事，披露了一个不起眼的学生课题如何最终转化为价值数百万美元的超级计算机的过程：科学创意的形成，克服重重技术障碍，研制弈棋机过程中的竞争和激烈的争执，最终战胜世界上最伟大的人类棋手。

人工智能经常被人们认为是计算机科学中的一门高度复杂甚至令人生畏的学科。长期以来人工智能方面的书籍往往包含复杂矩阵代数和微分方程。本书形成于作者多年来给没有多少微积分知识的学生授课时所用的讲义，它假定读者预先没有编程的经验，并说明了智能系统中的大部分基础知识实际上是简单易懂的。 　　本书目前已经被国际上多所大学(例如，德国的马德堡大学、日本的广岛大学、美国的波士顿大学和罗切斯特理工学院)采用。 如果你正在寻找关于人工智能或智能系统设计课程的浅显易懂的入门级教材，如果你不是计算机科学领域的专业人员，而又正在寻找介绍基于知识系统最新技术发展的自学指南，本书将是最佳选择。 　　本书是关于人工智能的教科书，浅显易懂、内容全面、案例丰富、参考文献详尽，不仅适合人工智能的初学者学习，而且也非常适合非计算机背景相关学科的研究人员参考。

The Most Human Human is a provocative, exuberant, and profound exploration of the ways in which computers are reshaping our ideas of what it means to be human. Its starting point is the annual Turing Test, which pits artificial intelligence programs against people to determine if computers can “think.” Named for computer pioneer Alan Turing, the Turing Test convenes a panel of judges who pose questions—ranging anywhere from celebrity gossip to moral conundrums—to hidden contestants in an attempt to discern which is human and which is a computer. The machine that most often fools the panel wins the Most Human Computer Award. But there is also a prize, bizarre and intriguing, for the Most Human Human. In 2008, the top AI program came short of passing the Turing Test by just one astonishing vote. In 2009, Brian Christian was chosen to participate, and he set out to make sure Homo sapiens would prevail. The author’s quest to be deemed more human than a computer opens a window onto our own nature. Interweaving modern phenomena like customer service “chatbots” and men using programmed dialogue to pick up women in bars with insights from fields as diverse as chess, psychiatry, and the law, Brian Christian examines the philosophical, biological, and moral issues raised by the Turing Test. One central definition of human has been “a being that could reason.” If computers can reason, what does that mean for the special place we reserve for humanity?

When it was first published in 1972, Hubert Dreyfus's manifesto on the inherent inability of disembodied machines to mimic higher mental functions caused an uproar in the artificial intelligence community. The world has changed since then. Today it is clear that "good old-fashioned AI," based on the idea of using symbolic representations to produce general intelligence, is in decline (although several believers still pursue its pot of gold), and the focus of the Al community has shifted to more complex models of the mind. It has also become more common for AI researchers to seek out and study philosophy. For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings. What Computers Can't Do was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.Hubert L. Dreyfus, who is Professor of Philosophy at the University of California, Berkeley, is also the author of Being-in-the-World. A Commentary on Heidegger's Being and Time, Division I.

陕西科技出版社最新引进美国图书《人工智能的未来》（On Intelligence）一书，是由杰夫•霍金斯，一位在硅谷极其成功、受人尊敬的计算机工程师、企业家与桑德拉•布拉克斯莉，《纽约日报》的栏目作家共同撰写。本书对人类大脑皮层所具有的知觉、认识、行为和智能功能新理论提出了新的理论构想。这一理论的独到之处在于对大脑皮层的现行认识提出了新的观点，对大脑的工作原理，即霍金斯称之为“真正智能”而非计算机式的人工智能立论扎实，观点独特、新颖，阐述精密。对大脑及其工作原理感兴趣的朋友不妨读读，必有收获。 本书共八章，人工智能、神经网络、人脑、记忆、智能理论新架构、大脑皮层工作原理、意识和创造力、智能之未来。

《身体的智能:智能科学新视角》采用易于理解的非技术化语言，通过介绍大量例子以及建立在机器人学、生物学、神经科学和心理学最新发展成果之上的基本概念，来阐述关于智能的可行理论。书中还介绍了这一理论在普适计算、经济与管理学以及人类记忆的心理学领域中的应用。两位作者描述的具身性智能对我们理解自然智能和人工智能都具有重要意义。 我们的大脑控制着身体，人尽皆知，那么我们的身体又是如何影响思维的呢?Rolf Pfeifer和Josh Bongard两位作者将通过《身体的智能:智能科学新视角》向您揭示我们的思想并非独立于身体，而是受到身体的紧密约束和激励。他们认为我们所能具有的种种思想都是基于具身性——我们身体的形态和材质特性。 《身体的智能:智能科学新视角》可供人工智能领域的科研工作者及研究生参考，也可供相关专业的科研人员参考。

Minds, Brains and Science takes up just the problems that perplex people, and it does what good philosophy always does: it dispels the illusion caused by the specious collision of truths. How can we accept an intuitive commonsense view of ourselves as conscious, free, rational agents in a universe that science tells us consists of mindless physical particles? Searle briskly and lucidly sets out his arguments against the familiar positions in the philosophy of mind, and details the consequences of his ideas for the mind-body problem, artificial intelligence, cognitive science, and the philosophy of the social sciences. Searle's book is an admirably clear and vigorous exposition of his views on a connected set of philosophical issues of importance and timeliness. --John Perry This book is aggressive, zealous, and acute. Searle's manner is that of a plain man in possession of plain truths that no one can reject if they are plainly enough stated. I cannot think of another book quite like it. --Arthur Danto

不远的将来，人工智能机器的智能将是人类的万亿个万亿倍，它们面对我们，并不像我们面对狗，而是如同我们面对蚊子、跳蚤甚至岩石，当它们消灭我们的时候，如同我们将蚊子拍死，将臭虫冲进下水道，谁会在消灭跳蚤的时候觉得这样太残忍了呢？！这也许是人类逃脱不了的宿命，这也使德·加里斯教授认为有责任写这本书。我知道如果不让地球上每个人都对这个关乎人类存亡的问题知情并且思考，那么书中所描写的比所有科幻电影更刺激、可怕的事情很有可能发生，甚至更加糟糕。希望每个人都来关注，希望每个人都来思考，希望这一切都还来得及……

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Click on "Features" tab below for more information Resources: Visit the author's website http://aima.cs.berkeley.edu/ to access both student and instructor resources including Power Point slides, syllabus. homework and exams, and solutions text problems.

编辑推荐：人工智能哲学是伴随现代信息理论和计算机技术发展起来的一个哲学分支。本书收集了人工智能研究领域著名学者的十五篇代表性论文，这些论文为计算机科学的发展和人工智能哲学的建立作出了开创性的贡献。这些文章总结了人工智能发展的历程，近年来该学科发展的趋势，以及人工智能中的重要课题。在这些划时代的著作中，包括有：现代计算机理论之父艾伦·图灵的“计算机与智能”；著名美国哲学家塞尔的“心灵，大脑与程序”；

集智俱乐部是一个从事学术研究、享受科学乐趣的探索者组成的团体，倡导以平等开放的态度、科学实证的精神进行跨学科的研究与交流，力图搭建一个中国的“没有围墙的研究所”。这些令人崇敬的、充满激情与梦想的集智俱乐部成员将带你了解图灵机模型、冯•诺依曼计算机体系结构、怪圈与哥德尔定理、通用人工智能、深度学习、人类计算与自然语言处理，与你一起展开一场令人热血沸腾的科学之旅。

《人工智能哲学》收集了人工智能研究领域著名学者的15篇代表性论文，这些论文为计算机科学的发展和人工智能哲学的建立做出了开创性的贡献。人工智能哲学是伴随现代信息理论和计算机技术发展起来的一个哲学分支。

群体智能是近年来发展迅速的人工智能学科领域.通过研究分散,自组织的动物群体和人类社会的智能行为, 学者们提出了许多迥异于传统思路的智能算法, 很好地解决了不少原来非常棘手的复杂工程问题.与蚁群算法齐名的粒子群优化(particle swarm optimization, 简称PSO)算法就是其中最受瞩目,应用最为广泛的成果之一. 本书由粒子群优化算法之父撰写,是该领域毋庸置疑的经典著作.作者提出,人类智能来源于社会环境中个体之间的交互,这种智能模型可以有效的应用到人工智能系统中去. 书中首先从社会心理学, 认知科学和演化计算等多个角度阐述了这种新方法的基础,然后详细说明了应用这些理论和模型所得出的新的计算智能方法--粒子群优化,进而深入探讨了将粒子群优化应用于广泛的工程问题.

How could the body influence our thinking when it seems obvious that the brain controls the body? In How the Body Shapes the Way We Think, Rolf Pfeifer and Josh Bongard demonstrate that thought is not independent of the body but is tightly constrained, and at the same time enabled, by it. They argue that the kinds of thoughts we are capable of have their foundation in our embodiment--in our morphology and the material properties of our bodies.This crucial notion of embodiment underlies fundamental changes in the field of artificial intelligence over the past two decades, and Pfeifer and Bongard use the basic methodology of artificial intelligence--"understanding by building"--to describe their insights. If we understand how to design and build intelligent systems, they reason, we will better understand intelligence in general. In accessible, nontechnical language, and using many examples, they introduce the basic concepts by building on recent developments in robotics, biology, neuroscience, and psychology to outline a possible theory of intelligence. They illustrate applications of such a theory in ubiquitous computing, business and management, and the psychology of human memory. Embodied intelligence, as described by Pfeifer and Bongard, has important implications for our understanding of both natural and artificial intelligence.

随着人工智能程序AlphaGo以4:1的大比分战胜人类围棋世界冠军李世石，机器将征服人类的担忧正在甚嚣尘上。《走近2050》则为我们描绘了一幅人机和谐共生、协同演化的全新场景。在看得见的未来，人类将越来越多地沉浸于五花八门的虚拟世界以获取各式体验，与此同时，我们将心甘情愿地将自己的注意力源源不断地输入给机器世界以促使它们进化。

本书以人工智能发展过程和该领域具有标志性意义的科学家为线索，向人们介绍了该学科在整个发展过程中的许多重大事件。它既可以为相关研究提供参考，同时也不失为一部饶有趣味的科学普及书籍。

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial intelligence adds a chapter that sorts out the current themes and tools -- chaos, adaptive systems, genetic algorithms -- for analyzing complexity and complex systems.There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter "Economic Reality" has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems.