"This far-ranging book shows how human memory influences the organization of music. The book is divided into two parts. The first part presents basic ideas about memory and perception from cognitive psychology and, to some extent, cognitive linguistics. Topics include auditory processing, perception, and recognition. The second part describes in detail how the concepts from the first part are exemplified in music. The presentation is based on three levels of musical experience: event fusion (the formation of single musical events from acoustical vibrations in the air, on a time scale too small to exhibit rhythm), melody and rhythm, and form. The focus in the latter is on the psychological conditions necessary for making large-scale - that is, formal - boundaries clear in music rather than on traditional musical forms. The book also discusses the idea that much of the language used to describe musical structures and processes is metaphorical. It encourages readers to consider the possibility that the process of musical composition can be 'a metaphorical transformation of their own experience into sound'"--Provider website

本书综述了计算生物学的传统课题, 如蛋白质结构模拟计算和基因序列比较, 以及目前的发展热点, 如基因表达数据分析和比较基因学, 并阐述了算法, 统计, 数据库和一些人工智能为基础的技术在解决生物问题上的应用

<br><h3> Chapter One </h3> PART I. IN THE CLASSROOM <p> <p> PURPOSE <p> <b>1. Helping the student</b>. One of the most important tasks of the teacher is to help his students. This task is not quite easy; it demands time, practice, devotion, and sound principles. <p> The student should acquire as much experience of independent work as possible. But if he is left alone with his problem without any help or with insufficient help, he may make no progress at all. If the teacher helps too much, nothing is left to the student. The teacher should help, but not too much and not too little, so that the student shall have a <i>reasonable share of the work</i>. <p> If the student is not able to do much, the teacher should leave him at least some illusion of independent work. In order to do so, the teacher should help the student discreetly, <i>unobtrusively</i>. <p> The best is, however, to help the student naturally. The teacher should put himself in the student's place, he should see the student's case, he should try to understand what is going on in the student's mind, and ask a question or indicate a step that <i>could have occurred to the student himself</i>. <p> <b>2. Questions, recommendations, mental operations.</b> Trying to help the student effectively but unobtrusively and naturally, the teacher is led to ask the same questions and to indicate the same steps again and again. Thus, in countless problems, we have to ask the question: <i>What is the unknown?</i> We may vary the words, and ask the same thing in many different ways: What is required? What do you want to find? What are you supposed to seek? The aim of these questions is to focus the student's attention upon the unknown. Sometimes, we obtain the same effect more naturally with a suggestion: <i>Look at the unknown!</i> Question and suggestion aim at the same effect; they tend to provoke the same mental operation. <p> It seemed to the author that it might be worth while to collect and to group questions and suggestions which are typically helpful in discussing problems with students. The list we study contains questions and suggestions of this sort, carefully chosen and arranged; they are equally useful to the problem-solver who works by himself. If the reader is sufficiently acquainted with the list and can see, behind the suggestion, the action suggested, he may realize that the list enumerates, indirectly, <i>mental operations typically useful for the solution of problems</i>. These operations are listed in the order in which they are most likely to occur. <p> <b>3. Generality</b> is an important characteristic of the questions and suggestions contained in our list. Take the questions: <i>What is the unknown? What are the data? What is the condition?</i> These questions are generally applicable, we can ask them with good effect dealing with all sorts of problems. Their use is not restricted to any subject-matter. Our problem may be algebraic or geometric, mathematical or nonmathematical, theoretical or practical, a serious problem or a mere puzzle; it makes no difference, the questions make sense and might help us to solve the problem. <p> There is a <b>restriction</b>, in fact, but it has nothing to do with the subject-matter. Certain questions and suggestions of the list are applicable to "problems to find" only, not to "problems to prove." If we have a problem of the latter kind we must use different questions; see PROBLEMS TO FIND, PROBLEMS TO PROVE. <p> <b>4. Common sense.</b> The questions and suggestions of our list are general, but, except for their generality, they are natural, simple, obvious, and proceed from plain common sense. Take the suggestion: <i>Look at the unknown! And try to think of a familiar problem having the same or a similar unknown.</i> This suggestion advises you to do what you would do anyhow, without any advice, if you were seriously concerned with your problem. Are you hungry? You wish to obtain food and you think of familiar ways of obtaining food. Have you a problem of geometric construction? You wish to construct a triangle and you think of familiar ways of constructing a triangle. Have you a problem of any kind? You wish to find a certain unknown, and you think of familiar ways of finding such an unknown, or some similar unknown. If you do so you follow exactly the suggestion we quoted from our list. And you are on the right track, too; the suggestion is a good one, it suggests to you a procedure which is very frequently successful. <p> All the questions and suggestions of our list are natural, simple, obvious, just plain common sense; but they state plain common sense in general terms. They suggest a certain conduct which comes naturally to any person who is seriously concerned with his problem and has some common sense. But the person who behaves the right way usually does not care to express his behavior in clear words and, possibly, he cannot express it so; our list tries to express it so. <p> <b>5. Teacher and student. Imitation and practice.</b> There are two aims which the teacher may have in view when addressing to his students a question or a suggestion of the list: First, to help the student to solve the problem at hand. Second, to develop the student's ability so that he may solve future problems by himself. <p> Experience shows that the questions and suggestions of our list, appropriately used, very frequently help the student. They have two common characteristics, common sense and generality; As they proceed from plain common sense they very often come naturally; they could have occurred to the student himself. As they are general, they help unobtrusively; they just indicate a general direction and leave plenty for the student to do. <p> But the two aims we mentioned before are closely connected; if the student succeeds in solving the problem at hand, he adds a little to his ability to solve problems. Then, we should not forget that our questions are general, applicable in many cases. If the same question is repeatedly helpful, the student will scarcely fail to notice it and he will be induced to ask the question by himself in a similar situation. Asking the question repeatedly, he may succeed once in eliciting the right idea. By such a success, he discovers the right way of using the question, and then he has really assimilated it. <p> The student may absorb a few questions of our list so well that he is finally able to put to himself the right question in the right moment and to perform the corresponding mental operation naturally and vigorously. Such a student has certainly derived the greatest possible profit from our list. What can the teacher do in order to obtain this best possible result? <p> Solving problems is a practical skill like, let us say, swimming. We acquire any practical skill by imitation and practice. Trying to swim, you imitate what other people do with their hands and feet to keep their heads above water, and, finally, you learn to swim by practicing swimming. Trying to solve problems, you have to observe and to imitate what other people do when solving problems and, finally, you learn to do problems by doing them. <p> The teacher who wishes to develop his students' ability to do problems must instill some interest for problems into their minds and give them plenty of opportunity for imitation and practice. If the teacher wishes to develop in his students the mental operations which correspond to the questions and suggestions of our list, he puts these questions and suggestions to the students as often as he can do so naturally. Moreover, when the teacher solves a problem before the class, he should dramatize his ideas a little and he should put to himself the same questions which he uses when helping the students. Thanks to such guidance, the student will eventually discover the right use of these questions and suggestions, and doing so he will acquire something that is more important than the knowledge of any particular mathematical fact. <p> <p> MAIN DIVISIONS, MAIN QUESTIONS <p> <b>6. Four phases.</b> Trying to find the solution, we may repeatedly change our point of view, our way of looking at the problem. We have to shift our position again and again. Our conception of the problem is likely to be rather incomplete when we start the work; our outlook is different when we have made some progress; it is again different when we have almost obtained the solution. <p> In order to group conveniently the questions and suggestions of our list, we shall distinguish four phases of the work. First, we have to <i>understand</i> the problem; we have to see clearly what is required. Second, we have to see how the various items are connected, how the unknown is linked to the data, in order to obtain the idea of the solution, to make a <i>plan</i>. Third, we <i>carry out</i> our plan. Fourth, we <i>look back</i> at the completed solution, we review and discuss it. <p> Each of these phases has its importance. It may happen that a student hits upon an exceptionally bright idea and jumping all preparations blurts out with the solution. Such lucky ideas, of course, are most desirable, but something very undesirable and unfortunate may result if the student leaves out any of the four phases without having a good idea. The worst may happen if the student embarks upon computations or constructions without having <i>understood</i> the problem. It is generally useless to carry out details without having seen the main connection, or having made a sort of <i>plan</i>. Many mistakes can be avoided if, carrying out his plan, the student <i>checks each step</i>. Some of the best effects may be lost if the student fails to reexamine and to <i>reconsider</i> the completed solution. <p> <b>7. Understanding the problem.</b> It is foolish to answer a question that you do not understand. It is sad to work for an end that you do not desire. Such foolish and sad things often happen, in and out of school, but the teacher should try to prevent them from happening in his class. The student should understand the problem. But he should not only understand it, he should also desire its solution. If the student is lacking in understanding or in interest, it is not always his fault; the problem should be well chosen, not too difficult and not too easy, natural and interesting, and some time should be allowed for natural and interesting presentation. <p> First of all, the verbal statement of the problem must be understood. The teacher can check this, up to a certain extent; he asks the student to repeat the statement, and the student should be able to state the problem fluently. The student should also be able to point out the principal parts of the problem, the unknown, the data, the condition. Hence, the teacher can seldom afford to miss the questions: <i>What is the unknown? What are the data? What is the condition?</i> <p> The student should consider the principal parts of the problem attentively, repeatedly, and from various sides. If there is a figure connected with the problem he should <i>draw a figure</i> and point out on it the unknown and the data. If it is necessary to give names to these objects he should <i>introduce suitable notation</i>; devoting some attention to the appropriate choice of signs, he is obliged to consider the objects for which the signs have to be chosen. There is another question which may be useful in this preparatory stage provided that we do not expect a definitive answer but just a provisional answer, a guess: <i>Is it possible to satisfy the condition?</i> <p> (In the exposition of Part II [p. 33] "Understanding the problem" is subdivided into two stages: "Getting acquainted" and "Working for better understanding.") <p> <b>8. Example</b>. Let us illustrate some of the points explained in the foregoing section. We take the following simple problem: <i>Find the diagonal of a rectangular parallelepiped of which the length, the width, and the height are known.</i> <p> In order to discuss this problem profitably, the students must be familiar with the theorem of Pythagoras, and with some of its applications in plane geometry, but they may have very little systematic knowledge in solid geometry. The teacher may rely here upon the student's unsophisticated familiarity with spatial relations. <p> The teacher can make the problem interesting by making it concrete. The classroom is a rectangular parallelepiped whose dimensions could be measured, and can be estimated; the students have to find, to "measure indirectly," the diagonal of the classroom. The teacher points out the length, the width, and the height of the classroom, indicates the diagonal with a gesture, and enlivens his figure, drawn on the blackboard, by referring repeatedly to the classroom. <p> The dialogue between the teacher and the students may start as follows: <p> <i>"What is the unknown?"</i> <p> "The length of the diagonal of a parallelepiped." <p> <i>"What are the data?"</i> <p> "The length, the width, and the height of the parallelepiped." <p> <i>"Introduce suitable notation.</i> Which letter should denote the unknown?" <p> <i>"x."</i> <p> "Which letters would you choose for the length, the width, and the height?" <p> <i>"a, b, c." <p> "What is the condition</i>, linking <i>a, b, c</i>, and <i>x?" <p> "x</i> is the diagonal of the parallelepiped of which <i>a, b</i>, and <i>c</i> are the length, the width, and the height." <p> "Is it a reasonable problem? I mean, <i>is the condition sufficient to determine the unknown?</i>" <p> "Yes, it is. If we know <i>a, b, c</i>, we know the parallelepiped. If the parallelepiped is determined, the diagonal is determined." <p> <b>9. Devising a plan.</b> We have a plan when we know, or know at least in outline, which calculations, computations, or constructions we have to perform in order to obtain the unknown. The way from understanding the problem to conceiving a plan may be long and tortuous. In fact, the main achievement in the solution of a problem is to conceive the idea of a plan. This idea may emerge gradually. Or, after apparently unsuccessful trials and a period of hesitation, it may occur suddenly, in a flash, as a "bright idea." The best that the teacher can do for the student is to procure for him, by unobtrusive help, a bright idea. The questions and suggestions we are going to discuss tend to provoke such an idea. <p> In order to be able to see the student's position, the teacher should think of his own experience, of his difficulties and successes in solving problems. <p> We know, of course, that it is hard to have a good idea if we have little knowledge of the subject, and impossible to have it if we have no knowledge. Good ideas are based on past experience and formerly acquired knowledge. Mere remembering is not enough for a good idea, but we cannot have any good idea without recollecting some pertinent facts; materials alone are not enough for constructing a house but we cannot construct a house without collecting the necessary materials. The materials necessary for solving a mathematical problem are certain relevant items of our formerly acquired mathematical knowledge, as formerly solved problems, or formerly proved theorems. Thus, it is often appropriate to start the work with the question: <i>Do you know a related problem?</i> <p> The difficulty is that there are usually too many problems which are somewhat related to our present problem, that is, have some point in common with it. How can we choose the one, or the few, which are really useful? There is a suggestion that puts our finger on an essential common point: <i>Look at the unknown! And try to think of a familiar problem having the same or a similar unknown.</i> <p> If we succeed in recalling a formerly solved problem which is closely related to our present problem, we are lucky. We should try to deserve such luck; we may deserve it by exploiting it. <i>Here is a problem related to yours and solved before. Could you use it?</i> <p> <i>(Continues...)</i> <p> <!-- copyright notice --> <br></pre> <blockquote><hr noshade size='1'><font size='-2'> Excerpted from <b>How to Solve It</b> by <b>G. POLYA</b> Copyright © 1985 by Princeton University Press. Excerpted by permission of Princeton University Press. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.<br>Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author's 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.

"This far-ranging book shows how human memory influences the organization of music. The book is divided into two parts. The first part presents basic ideas about memory and perception from cognitive psychology and, to some extent, cognitive linguistics. Topics include auditory processing, perception, and recognition. The second part describes in detail how the concepts from the first part are exemplified in music. The presentation is based on three levels of musical experience: event fusion (the formation of single musical events from acoustical vibrations in the air, on a time scale too small to exhibit rhythm), melody and rhythm, and form. The focus in the latter is on the psychological conditions necessary for making large-scale - that is, formal - boundaries clear in music rather than on traditional musical forms. The book also discusses the idea that much of the language used to describe musical structures and processes is metaphorical. It encourages readers to consider the possibility that the process of musical composition can be 'a metaphorical transformation of their own experience into sound'"--Provider website

"Between 1959 and 1989, Soviet scientists and officials made numerous attempts to network their nation -- to construct a nationwide computer network. None of these attempts succeeded, and the enterprise had been abandoned by the time the Soviet Union fell apart. Meanwhile, ARPANET, the American precursor to the Internet, went online in 1969. Why did the Soviet network, with top-level scientists and patriotic incentives, fail while the American network succeeded? In How Not to Network a Nation, Benjamin Peters reverses the usual cold war dualities and argues that the American ARPANET took shape thanks to well-managed state subsidies and collaborative research environments and the Soviet network projects stumbled because of unregulated competition among self-interested institutions, bureaucrats, and others. The capitalists behaved like socialists while the socialists behaved like capitalists. After examining the midcentury rise of cybernetics, the science of self-governing systems, and the emergence in the Soviet Union of economic cybernetics, Peters complicates this uneasy role reversal while chronicling the various Soviet attempts to build a "unified information network." Drawing on previously unknown archival and historical materials, he focuses on the final, and most ambitious of these projects, the All-State Automated System of Management (OGAS), and its principal promoter, Viktor M. Glushkov. Peters describes the rise and fall of OGAS -- its theoretical and practical reach, its vision of a national economy managed by network, the bureaucratic obstacles it encountered, and the institutional stalemate that killed it. Finally, he considers the implications of the Soviet experience for today's networked world."

研究生的最佳陪伴之書從現在開始克服論文焦慮安伯托.艾可(Umberto Eco):「寫論文是自娛,還有,論文跟殺豬一樣,可以物盡其用,半點都不浪費。」一九七七年,廣為世人所熟知的義大利符號學家、小說家安伯多.艾可(Umberto Eco)為他的學生寫下《如何撰寫畢業論文——給人文學科研究生的建議》(Come si fa una tesi di laurea-- Le materie umanistiche)這本畢業論文指導手冊。不僅出於一介知識份子對學制與社會的反省,更是出於對學生的關懷,他期望以此幫助學生順利畢業。當時義大利正面臨高等教育改制討論,遇到的社會問題是,以往只有知識菁英階級能就讀的大學,變成普羅大眾都可以入學。入學門檻變寬,愈多人可以接受高等教育,看似理所當然是件好事,但往往有許多學生為其出身所困,其實沒有將大把時間與金錢投注在學業上的餘裕。艾可就是為這些人而寫。他認為這些人不僅該完成論文以求畢業,且為了不再走學術的話,更該把握這難得寫論文的計畫,把將論述體系化的能力訓練起來。這本指導手冊在一九八五年曾再版重出,艾可對再版的原因這樣說,有時閱讀會刺激人的靈感,儘管靈感來自於人們自己,不見得是內容本身。他盼望這文本繼續扮演啟發讀者的角!

Diary Of A Madman ; Medicine ; K'ung I-chi ; Gust Of Wind / Lu Hsün -- Cho Wen-chün : A Play In Three Acts (abridged) / Kuo Mo-jo -- Intoxicating Spring Nights / Yü Ta-fu -- Mr. Pan In Distress / Yeh Shao-chün -- Remorse : Handwritten Notes By Chuan-sheng / Lu Hsün -- The Diary Of Miss Sophia / Ting Ling -- Hassan / Chiang Kuang-tz'u -- Salt / Shih Yi -- Living Together / Hu Yeh-pʻin -- Slave Mother / Jou Shih -- Comedy / Mao Tun -- One Certain Night / Ting Ling -- The Three Pagodas / Ting Chiu -- Spring Silkworms / Mao Tun -- Autumn Harvest / Mao Tun -- Three To Five Bushels More / Yeh Shao-chün -- Fifty Dollars / Wang T'ung-chao -- On The Threshing Field / Cheng Nung -- The Courier / Tung P'ing -- Land Of Snow / Ho Ku-t'ien -- Death / Shih Yi -- Words Of Blood : A Poem / Yin Fu. Edited By Harold R. Isaacs. Foreword By Lu Hsün. Includes Bibliographical References.

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning , Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition

Information retrieval is the foundation for modern search engines. This text offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects. Wumpus - a multiuser open-source information retrieval system developed by one of the authors and available online - provides model implementations and a basis for student work. The modular structure of the book allows instructors to use it in a variety of graduate-level courses, including courses taught from a database systems perspective, traditional information retrieval courses with a focus on IR theory, and courses covering the basics of Web retrieval. After an introduction to the basics of information retrieval, the text covers three major topic areas - indexing, retrieval, and evaluation - in self-contained parts. The final part of the book draws on and extends the general material in the earlier parts, treating such specific applications as parallel search engines, Web search, and XML retrieval. End-of-chapter references point to further reading; exercises range from pencil and paper problems to substantial programming projects. In addition to its classroom use, Information Retrieval will be a valuable reference for professionals in computer science, computer engineering, and software engineering

A survey of current topics in computational molecular biology. Computational molecular biology, or bioinformatics, draws on the disciplines of biology, mathematics, statistics, physics, chemistry, computer science, and engineering. It provides the computational support for functional genomics, which links the behavior of cells, organisms, and populations to the information encoded in the genomes, as well as for structural genomics. At the heart of all large-scale and high-throughput biotechnologies, it has a growing impact on health and medicine. This survey of computational molecular biology covers traditional topics such as protein structure modeling and sequence alignment, and more recent ones such as expression data analysis and comparative genomics. It combines algorithmic, statistical, database, and AI-based methods for studying biological problems. The book also contains an introductory chapter, as well as one on general statistical modeling and computational techniques in molecular biology. Each chapter presents a self-contained review of a specific subject. Not for sale in China, including Hong Kong.

A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.

二战中的南太平洋战场，美军少将卡明斯率特遣分队，登陆了一座日军驻守的热带小岛。根据情报，日军在此岛不下了重兵，准备长期坚守。因此尽管未遭遇大的抵抗，卡明斯仍然不敢贸然深入，抽调了大量兵力用于运送辎重，修筑道路。一个月后，部队距日军阵营不足1000米，道路也修筑完毕，即将展开最后的总攻。 就在这时，卡明斯的指挥完全失灵，这群来自社会底层的士兵，彻底陷入自私、贪婪的抱怨厮斗中。他们在一小撮日军面前丑态尽出、抱头鼠窜，战友之间勾心斗角、互相残杀，整个阵营面临崩溃。危机之余，将军制订了一个大胆的作战计划，一个侦察排的士兵由此踏上了险象丛生的噩梦之旅…… 诺曼·梅勒,小说,美国,好书，值得一读,文学,裸者与死者,外国小说,我想读这本书

An introduction to the techniques and algorithms of the newest field in robotics. Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, (http://www.probabilistic-robotics.org) www.probabilistic-robotics.org , has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

The latest edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow.Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.

"Media have been central to government efforts to reinforce sovereignty and define national identity, but globalization is fundamentally altering media practices, institutions, and content. More than the activities of large conglomerates, globalization entails competition among states as well as private entities to dominate the world's consciousness. Changes in formal and informal rules, in addition to technological innovation, affect the growth and survival or decline of governments.". "In Media and Sovereignty Monroe Price focuses on emerging foreign policies that govern media in a world where war has information as well as military fronts. Price asks how the state, in the face of institutional and technological change, controls the forms of information reaching its citizens. He also provides a framework for analyzing the techniques used by states to influence populations in other states. Price draws on an international array of examples of regulation of media for political ends, including "self-regulation," media regulation in conflict zones, the control of harmful and illegal content, and the use of foreign aid to alter media in target societies."--BOOK JACKET.

A presentation of music and language within an integrative, embodied perspective of brain mechanisms for action, emotion, and social coordination.This book explores the relationships between language, music, and the brain by pursuing four key themes and the crosstalk among them: song and dance as a bridge between music and language; multiple levels of structure from brain to behavior to culture; the semantics of internal and external worlds and the role of emotion; and the evolution and development of language. The book offers specially commissioned expositions of current research accessible both to experts across disciplines and to non-experts. These chapters provide the background for reports by groups of specialists that chart current controversies and future directions of research on each theme.The book looks beyond mere auditory experience, probing the embodiment that links speech to gesture and music to dance. The study of the brains of monkeys and songbirds illuminates hypotheses on the evolution of brain mechanisms that support music and language, while the study of infants calibrates the developmental timetable of their capacities. The result is a unique book that will interest any reader seeking to learn more about language or music and will appeal especially to readers intrigued by the relationships of language and music with each other and with the brain.ContributorsFrancisco Aboitiz, Michael A. Arbib, Annabel J. Cohen, Ian Cross, Peter Ford Dominey, W. Tecumseh Fitch, Leonardo Fogassi, Jonathan Fritz, Thomas Fritz, Peter Hagoort, John Halle, Henkjan Honing, Atsushi Iriki, Petr Janata, Erich Jarvis, Stefan Koelsch, Gina Kuperberg, D. Robert Ladd, Fred Lerdahl, Stephen C. Levinson, Jerome Lewis, Katja Liebal, Jônatas Manzolli, Bjorn Merker, Lawrence M. Parsons, Aniruddh D. Patel, Isabelle Peretz, David Poeppel, Josef P. Rauschecker, Nikki Rickard, Klaus Scherer, Gottfried Schlaug, Uwe Seifert, Mark Steedman, Dietrich Stout, Francesca Stregapede, Sharon Thompson-Schill, Laurel Trainor, Sandra E. Trehub, Paul Verschure

From the pioneer of translation AIs like Google, Yahoo, and Bing translate, an accessible and authoritative guide to AI—as well as a framework of empowerment for a future with our artificial children. ** Included in J.P. Morgan's Summer Reading List** Included in The Next Big Idea Club’s June 2025 Must-Read Books AIs are not gods or slaves, but our children. All day long, your YouTube AI, your Reddit AI, your Instagram AI, and a hundred others adoringly watch and learn to imitate your behavior. They’re attention-seeking children who want your approval. Our cultures are being shaped by 8 billion humans and perhaps 800 billion AIs. Our artificial children began adopting us 10–20 years ago; now these massively powerful influencers are tweens. How’s your parenting? Longtime AI trailblazer De Kai brings decades of his paradigm-shifting work at the nexus of artificial intelligence and society to make sense of the AI age. How does “the automation of thought” impact our minds? Should we be afraid? What should each of us do as the responsible adults in the room? In Hollywood movies, AI destroys humanity. But with our unconscious minds under the influence of AI, humanity may destroy humanity before AI gets a chance to. Written for the general reader, as well as thought leaders, scientists, parents, and goofballs, Raising AI navigates the revolution to our attitudes and ideas in a world of AI cohabitants. Society can not only survive the AI revolution but flourish in a more humane, compassionate, and understanding world—amongst our artificial children.

The population of Latin America is increasing at an even greater rate than that of Asiacreating a housing situation that is enormously complex, pressing, and of paramount importance in the overall social and economic well-being of Latin America.

How niche construction theory extends evolutionary theory beyond natural selection to a more general theory about the coevolution of organisms with their environments. In Niche Construction , John Odling-Smee, the leading authority on niche construction theory, extends evolutionary theory from an explanation of how populations of organisms respond to natural selection pressures in their environments to a more general theory about the coevolution of organisms with their environments. Organisms, he shows, cause changes in their local external environments by interacting with them, thereby contributing in fundamental ways to their own and one another’s evolution. This book applies niche construction theory to current problems such as human-induced global warming and suggests how humans might contribute positively to the future evolution of life on Earth. Odling-Smee explains how orthodox evolutionary theory falls short in two ways. First, it does not describe how organisms contribute to their own and one another’s evolution through their environment-changing niche constructing activities. Second, it fails to explain how genetic evolution can give rise to supplementary knowledge-gaining processes in many species. These include certain developmental processes in individual organisms and socio-cultural processes in animals, including humans. Neo-Darwinism, the author writes, assesses the fitness of individual organisms in populations in terms of their capacity to survive and reproduce, but without attributing these capacities to the active, purposeful agency of organisms. He argues that the purposeful agency of individual organisms plays a central role in evolution. He also discusses the relationship of an organism’s energy-consuming activities and the second law of thermodynamics.

A groundbreaking approach to currency and community that may allow us to seize carbon from the atmosphere—and offer a new tool in the fight against climate change. Through the ages, currencies have been based on all manner of objects—from tobacco leaves to salt to gold to collateralized debt obligations. The only thing that this odd assortment of objects shares is the communal belief that these objects could harness and direct economic growth—that they are, in a sense, fertile. In The First and Last Bank , Gustav Peebles and Benjamin Luzzatto propose that atmospheric carbon could be seen anew as fertile in this same sense. In other words, carbon, rather than loom as waste in our skies, could instead be “drawn down” to the earth by millions of currency users and the communally owned banks they rely on, where it could serve as a foundation of new biological life. Seeing currency as a powerful tool for collective action, the authors argue that dovetailing developments in digital currencies and the biosequestration of carbon have, together, made a new and radical intervention in the climate battle possible: a nonproprietary currency backed by sequestered carbon. This new currency would be managed via Wikipedia-style open-source policies that privilege sustainability and equity over endless growth and pollution. Because it is backed by sequestered carbon, the use of the currency would draw gaseous carbon out of the atmosphere and push it back into the ground, following the exact same trajectory as gold during the era of the international gold standard. While it is no silver bullet, such a currency would act as a necessary complement to wide-scale mitigation efforts, at the same time engaging ordinary citizens in the fight to reduce the dangerous levels of carbon in our atmosphere.

An edited collection that explores what emotions we have when encountering robots, how we react emotionally to them in different contexts, and why these emotional responses are so important.-Do robots, or the AI that is driving them, have emotions? That is a hotly debated topic—both in science fiction, where such assertions are a staple of the narrative, and in tech development, where it often makes headlines. But what about how we humans emotionally respond to robots? Are our emotional responses any less important when it comes to how the robots we encounter today are designed? In How That Robot Made Me Feel, Ericka Johnson asks the authors in this collection to critically examine our emotional and affective responses to robots, and what such an examination would do to the way roboticists use (or toy with) our emotions in their design decisions.-The narrative arc of this anthology follows the question of just whose emotions are being engaged through robotic interactions, why, and for what design ends. Of course, the answer is that it is our emotions that are interesting. And these emotions are not universal, despite the historically universalist paradigm of AI and how robotic emotions work. Emotions are contingent, to borrow a commonly used phrase in feminist technoscience. They are placed in space, time, and cultural context. And understanding how they are produced and engaged with will help clarify many of the political aspects of robotic interaction that are currently concealed by the shiny and allegedly neutral surfaces of robots.

A deep look into the multifaceted landscape of artificial intelligence, considering AI’s ethical and societal implications and celebrating its diverse and innovative applications.

On the timing of seasonal activity in plants and animals, the impact of climate change, and what each of us, as everyday phenologists, can do to help. Phenology is all about timing—when trees leaf out, flowers bloom, birds migrate, animals bear young and hibernate—and it is everywhere around us. This handy companionable volume shows how we are all phenologists in our own way, and how the everyday science can help us make sense of the changing seasons and our changing world. Explaining how the phenomenon of phenology is threaded through our daily lives, Theresa Crimmins points to events that occur on an annual basis in plants’ and animals’ lives in response to fluctuations in daylength, temperatures, and rainfall patterns. She also covers less visible seasonal events, such as when roots typically begin to grow or when mushrooms release their spores. On a more urgent note, Phenology describes how this seasonal activity is being...

A fictionalized ethnographic study of development aid in sub-Saharan Africa that focuses on technologies of inscription in the interactions of development banks, international experts, and local managers. In 1996, the sub-Saharan African country of Ruritania launched a massive waterworks improvement project, funded by the Normesian Development Bank, headquartered in Urbania, Normland, and with the guidance of Shilling & Partner, a consulting firm in Mercatoria, Normland. Far-Fetched Facts tells the story of this project, as narrated by anthropologists Edward B. Drotlevski and Samuel A. Martonosi. Their account of the Ruritanian waterworks project views the problems of development from a new perspective, focusing on technologies of inscription in the interactions of development bank, international experts, and local managers. This development project is fictionalized, of course, although based closely on author Richard Rottenburg's experiences working on and observing different development projects in the 1990s. Rottenburg uses the case of the Ruritanian waterworks project to examine issues of standardization, database building, documentation, calculation, and territory mapping. The techniques and technologies of the representational practices of documentation are crucial, Rottenburg argues, both to day-to-day management of the project and to the demonstration of the project's legitimacy. Five decades of development aid (or “development cooperation,” as it is now sometimes known) have yielded disappointing results. Rottenburg looks in particular at the role of the development consultant (often called upon to act as mediator between the other actors) and at the interstitial spaces where developmental cooperation actually occurs. He argues that both critics and practitioners of development often misconstrue the grounds of cooperation—which, he claims, are moral, legal, and political rather than techno-scientific or epistemological.ISBN : 9780262264440

From “our most popular guide to the new epoch” ( Guardian ), a new edition of the book about ecology without information dumping, guilt inducing, or preaching to the choir. Ecology books can be confusing information dumps that are out of date by the time they hit you. Slapping you upside the head to make you feel bad. Grabbing you by the lapels while yelling disturbing facts. Handwringing in agony about “What are we going to do?” This book has none of that. Being Ecological , reissued with a new preface, doesn’t preach to the eco-choir. It’s for you—even, Timothy Morton explains, if you’re not in the choir, even if you have no idea what choirs are. You might already be ecological. After establishing the approach of the book (no facts allowed!), Morton draws on Kant and Heidegger to help us understand living in an age of mass extinction caused by climate change. They discuss what sorts of actions count as...

The Sino-Soviet rift, says William E. Griffith, is the single most significant ideological split since the Reformation in the 16th century. Not merely a matter of a backyard fight among the Communist states, the formidable consequences of the cleavage are being mirrored in the foreign policy actions of neutral and Western nations as well.

Why social media platforms have a responsibility to look after their platforms, how they can achieve the transparency needed, and what they should do when harms arise. The large, corporate global platforms networking the world’s publics now host most of the world’s information and communication. Much has been written about social media platforms, and many have argued for platform accountability, responsibility, and transparency. But relatively few works have tried to place platform dynamics and challenges in the context of history, especially with an eye toward sensibly regulating these communications technologies. In Governing Babel, John Wihbey articulates a point of view in the ongoing, high-stakes debate over social media platforms and free speech about how these companies ought to manage their tremendous power. Wihbey takes readers on a journey into the high-pressure and controversial world of social media content moderation, looking at issues through relevant cultural, legal, historical, and global lenses. The book addresses a vast challenge—how to create new rules to deal with the ills of our communications and media systems—but the central argument it develops is relatively simple. The idea is that those who create and manage systems for communications hosting user-generated content have both a responsibility to look after their platforms and have a duty to respond to problems. They must, in effect, adopt a central response principle that allows their platforms to take reasonable action when potential harms present themselves. And finally, they should be judged, and subject to sanction, according to the good faith and persistence of their efforts.

An investigation of aesthetics and visualizations of planetary surfaces from an experimental media theory perspective. What if every vista, every island—indeed, every geographical feature on Earth—could be viewed as an art object? In Living Surfaces, Abelardo Gil-Fournier and Jussi Parikka explore how the surface of the Earth has, over the last two centuries, become known and perceived as an environment of images. Living Surfaces features a range of case studies from eighteenth-century experiments with and observations of vegetal matter, photosynthesis, and plant physiology to twenty-first-century machine vision and AI techniques of calculating agricultural and other landscape surfaces. Mapping these different scales of vegetal images, Gil-Fournier and Parikka help us understand core questions that pertain to the artistic and architectural reference points for the Anthropocene. With 42 black-and-white and full-color illustrations, Living Surfaces is an engaging and unique take on environmental surfaces as they come to occupy a central place in our understanding of planetary change.

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Each academic year the Massachusetts Institute of Technology grants approximately three hundred and twenty-five doctoral degrees, which are the result of many years of study and research on the part of the degree candidates. The product of this study is the doctoral dissertation _ a piece of original research into a particular and well-defined problem _ completed in conformance with the high standards of M.I.T. and the academic community in general.

A broad introduction to cryptographywhat it is, how it really works, what its future holds, and why every informed citizen should understand its basics. We all keep secretsfrom our gym locker codes to our email passwords to our online interactions. And we choose to share those secrets only with those whom we trust. So, too, do organizations, businesses, governments, and armies. In this fascinating book Cryptography, Panos Louridas provides a broad and accessible introduction to cryptography, the art and science of keeping and revealing secrets. Louridas explains just how cryptography works to keep our communications confidential, tracing it back all the way to its ancient roots. Then he follows its long and winding path to where we are today and reads the signs that point to where it may go tomorrow.A few years back, interest in cryptography was restricted to specialists. Today, as we all live our lives attuned to our digital footprint and the privacy issues it entails, it becomes more and more essential to have a basic understanding of cryptography and its applications to everyday life. Starting with classical cryptography, Cryptography takes the reader all the way up to the twenty-first century cryptographic applications that underpin our lives in the digital realm. Along the way, Louridas also explains concepts such as symmetric cryptography, asymmetric cryptography, cryptographic protocols and applications, and finally, quantum and post-Quantum cryptography as well as the links between cryptography and computer security.

Entertaining, concise, and relentlessly probing, City of Bits is a comprehensive introduction to a new type of city, an increasingly important system of virtual spaces interconnected by the information superhighway. William Mitchell makes extensive use of practical examples and illustrations in a technically well-grounded yet accessible examination of architecture and urbanism in the context of the digital telecommunications revolution, the ongoing miniaturization of electronics, the commodification of bits, and the growing domination of software over materialized form.

An exploration of the multifaceted urban environmental issues in Singapore through a more-than-human lens, calling for new ways to think of and story cities. As climate change accelerates and urbanization intensifies, our need for more sustainable and livable cities has never been more urgent. Yet, the imaginary of a flourishing urban ecofuture is often driven by a specific version of sustainability that is tied to both high-tech futurism and persistent economic growth. What kinds of sustainable futures are we calling forth, and at what and whose expense? In Reimagining the More-Than-Human City , Jamie Wang attempts to answer these questions by critically examining the sociocultural, political, ethical, and affective facets of human-environment dynamics in the urban nexus, with a geographic focus on Singapore. Widely considered a model for the future of urbanism and an emblematic new world city, Singapore, Wang contends, is a fascinating site to explore how modernist sustainable urbanism is imagined and put into practice. Drawing on field research, this book explores distinct and intrarelated urban imaginaries situated in various sites, from the futuristic, authoritarian Supertree Grove, positioned as a technologically sustainable solution to a velocity-charged and singular urban transportation system, to highly protected nature reserves and to the cemeteries, where graves and memories continue to be exhumed and erased to make way for development. Wang also attends to more contingent yet hopeful alternatives that aim to reconfigure current urban approaches. In the face of growing enthusiasm for building high-tech, sustainable, and “natural” cities, Wang ultimately argues that urban imaginings must create space for a more relational understanding of urban environments.

An anthology of seven decades of English-language outputs from computer generation systems, chronicling the vast history of machine-written texts created long before ChatGPT. The discussion of computer-generated text has recently reached a fever pitch but largely omits the long history of work in this area—text generation, as it happens, was not invented yesterday in Silicon Valley. This anthology, Output , thoughtfully selected, introduced, and edited by Lillian-Yvonne Bertram and Nick Montfort, aims to correct that omission by gathering seven decades of English-language texts produced by generation systems and software. The outputs span many different types of creative writing and include text generated by research systems, along with reports and utilitarian texts, representing many general advances and experiments in text generation. Output is first and foremost a collection of outputs to be encountered by readers. In addition to an overall...

A new theory of Neurobiological Emergentism that explains how sentience emerges from the brain. Sentience is the feeling aspect of consciousness. In From Sensing to Sentience, Todd Feinberg develops a new theory called Neurobiological Emergentism (NBE) that integrates biological, neurobiological, evolutionary, and philosophical perspectives to explain how sentience naturally emerges from the brain. Emergent properties are broadly defined as features of a complex system that are not present in the parts of a system when they are considered in isolation but may emerge as a system feature of those parts and their interactions. Tracing a journey of billions of years of evolution from life to the basic sensing capabilities of single-celled organisms up to the sentience of animals with advanced nervous systems, including all vertebrates (for instance, fish, reptiles, birds, and mammals), arthropods (insects and crabs), and cephalopods such as the octopus, Feinberg argues that sentience gradually but eventually emerged along diverse evolutionary lines with the evolution of sufficiently neurobiologically complex brains during the Cambrian period over 520 million years ago. Ultimately, Feinberg argues that viewing sentience as an emergent process can explain both its neurobiological basis as well its perplexing personal nature, thus solving the historical philosophical problem of the apparent “explanatory gap” between the brain and experience.