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介绍几个做AI了解到的牛人

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发表于 2011-9-6 21:39:56 | 显示全部楼层 |阅读模式
在这里说明一下,Herbert的学生是Allen Newell,Newell的学生John就是现在在AI方面超级猛的一个Professor。看来,学术有圈子啊,大家注意一下他们的毕业院校。真是让人羡慕死。
Herbert Simon                                                                                                                                        From Wikipedia, the free encyclopedia
                                                                                                                                                                                                                                                                                                                                                                                                                                For other people named Herbert Simon, see Herbert Simon (disambiguation).
Herbert Simon
Born
June 15, 1916
Milwaukee, Wisconsin, USA
Died
February 9, 2001 (aged 84)
Pittsburgh, Pennsylvania, USA
Nationality
United States
Fields
Artificial Intelligence
Cognitive psychology
Computer science
Economics
Political science
Institutions
Carnegie Mellon University 
University of California, Berkeley
Illinois Institute of Technology
University of Chicago
Henry Schultz
Doctoral students
Edward Feigenbaum
Allen Newell
David Bree
Known for
Logic Theory Machine
General Problem Solver
Bounded Rationality
Notable awards
Turing Award 1975
Nobel Prize in Economics 1978
National Medal of Science 1986
von Neumann Theory Prize 1988
Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics, management, philosophy of science, sociology, and political science. With almost a thousand very highly cited publications, he is one of the most influential social scientists of the 20th century.
Simon was among the founding fathers of several of today's important scientific domains, including artificial intelligence, information processing, decision-making, problem-solving, attention economics, organization theory, complex systems, and computer simulation of scientific discovery. He coined the terms bounded rationality and satisficing, and was the first to analyze the architecture of complexity and to propose a preferential attachment mechanism to explain power law distributions.
He also received many top-level honors later in life. These include: the ACM's Turing Award for making "basic contributions to artificial intelligence, the psychology of human cognition, and list processing" (1975); the Nobel Memorial Prize in Economics "for his pioneering research into the decision-making process within economic organizations" (1978); the National Medal of Science (1986); and the APA's Award for Outstanding Lifetime Contributions to Psychology (1993).
As a testament to his interdisciplinary approach, Simon was affiliated with such varied Carnegie Mellon departments as the School of Computer Science, Tepper School of Business, Departments of Philosophy, Social and Decision Sciences, and Psychology.
Contents [hide]
[edit] LifeHerbert Alexander Simon was born in Milwaukee, Wisconsin on June 15, 1916. His father, Arthur Simon (1881–1948), was an electrical engineer who had come to the United States from Germany in 1903 after earning his engineering degree from the Technische Hochschule of Darmstadt.[1] Arthur, an inventor who was granted "several dozen patents", was also an independent patent attorney.[2] Herbert's mother, Edna Marguerite Merkel, was an accomplished pianist whose ancestors had come from Prague and Cologne.[3] Herbert's European ancestors had been piano makers, goldsmiths, and vintners. Simon's father was Jewish and his mother came from a family of Jewish, Lutheran, and Catholic backgrounds.[4]
Herbert Simon was educated as a child in the public school system in Milwaukee where he developed an interest in science. He found schoolwork to be interesting but rather easy. Unlike many children, Simon was exposed to the idea that human behavior could be studied scientifically at a relatively young age due to the influence of his mother’s younger brother, Harold Merkel, who had studied economics at the University of Wisconsin–Madison under John R. Commons. Through his uncle’s books on economics and psychology, Simon discovered the social sciences. Simon received both his B.A. (1936) and his Ph.D. (1943) in political science, from the University of Chicago, where he studied under Harold Lasswell and Charles Edward Merriam.
Among his earliest influences, Simon has cited Richard Ely’s economics textbook, Norman Angell’s The Great Illusion, and Henry George’s Progress and Poverty. In 1933, Simon entered the University of Chicago, and following those early influences, he studied the social sciences and mathematics. He was interested in biology, but chose not to study it because of his "color-blindness and awkwardness in the laboratory".[5] He chose instead to focus on political science and economics. His most important mentor at the University was Henry Schultz who was an econometrician and mathematical economist. After enrolling in a course on "Measuring Municipal Governments," Simon was invited to be a research assistant for Clarence Ridley, with whom he coauthored the book Measuring Municipal Activities in 1948.[6] Eventually his studies led him to the field of organizational decision-making, which would become the subject of his doctoral dissertation.
From 1939 to 1942, Simon acted as director of a research group at the University of California, Berkeley. When the group’s grant was exhausted, he joined the faculty of Illinois Institute of Technology, where he was a professor of political science from 1942 to 1949, and also served as department chairman. Back in Chicago, he began participating in the seminars held by the staff of the Cowles Commission who at that time included Trygve Haavelmo, Jacob Marschak, and Tjalling Koopmans. He thus began a more in-depth study of economics in the area of institutionalism. Marschak brought Simon in to assist in the study he was currently undertaking with Sam Schurr of the “prospective economic effects of atomic energy”.
In 1949, Simon became a professor of administrations and chairman of the Department of Industrial Management at Carnegie Tech (later to become Carnegie Mellon University).[7] He continued to teach in various departments at Carnegie Mellon, including psychology and computer science, until his death in 2001.
From 1950 to 1955, Simon studied mathematical economics and during this time, together with David Hawkins, discovered and proved the Hawkins-Simon theorem on the “conditions for the existence of positive solution vectors for input-output matrices." He also developed theorems on near-decomposability and aggregation. Having begun to apply these theorems to organizations, Simon determined around 1954 that the best way to study problem-solving was to simulate it with computer programs, which led to his interest in computer simulation of human cognition. End 1950s he was among the first members of the Society for General Systems Research.
Simon was a member of the[8] First Unitarian Church of Pittsburgh. He had a keen interest in the arts. He was a friend of Robert Lepper[9] and Richard Rappaport and he influenced Lepper's interest in the impact of machine on society.[10] Rappaport also painted Simon's commissioned portrait[11] at Carnegie Mellon University.
[edit] Studying decision-making
Simons 3 stages in Rational Decision Making: Intelligence, Design, Choice (IDC)


Administrative Behavior[12] from 1947 was Herbert Simon’s doctoral dissertation and his first book. It served as the foundation for his life's work. The centerpiece of this book is the behavioral and cognitive processes of making rational human choices, that is, decisions. An operational administrative decision should be correct and efficient, and it must be practical to implement with a set of coordinated means.
Any decision involves a choice selected from a number of alternatives, directed toward an organizational goal or subgoal. Realistic options will have real consequences consisting of personnel actions or non-actions modified by environmental facts and values. In practice, some of the alternatives may be conscious or unconscious; some of the consequences may be unintended as well as intended; and some of the means and ends may be imperfectly differentiated, incompletely related, or poorly detailed.
The task of rational decision making is to select the alternative that results in the more preferred set of all the possible consequences. This task can be divided into three required steps:
  • the identification and listing of all the alternatives;
  • the determination of all the consequences resulting from each of the alternatives; and
  • the comparison of the accuracy and efficiency of each of these sets of consequences.[13]
Any given individual or organization attempting to implement this model in a real situation would be unable to comply with the three requirements. It is highly improbable that one could know all the alternatives, or all the consequences that follow each alternative.
The question here is: given the inevitable limits on rational decision making, what other techniques or behavioral processes can a person or organization bring to bear to achieve approximately the best result? Simon writes:
“The human being striving for rationality and restricted within the limits of his knowledge has developed some working procedures that partially overcome these difficulties. These procedures consist in assuming that he can isolate from the rest of the world a closed system containing a limited number of variables and a limited range of consequences.”[14]Administrative Behavior, as a text, addresses a wide range of human behaviors, cognitive abilities, management techniques, personnel policies, training goals and procedures, specialized roles, criteria for evaluation of accuracy and efficiency, and all of the ramifications of communication processes. Simon is particularly interested in how these factors directly and indirectly influence the making of decisions.
Weaving in and out of the practical functioning of all of these organizational factors are two universal elements of human social behavior that Simon addresses in Chapter VII—The Role of Authority,[15] and in Chapter X—Loyalties, and Organizational Identification.[16]
Authority is a well studied, primary mark of organizational behavior, and is straightforwardly defined in the organizational context as the ability and right of an individual of higher rank to determine the decision of an individual of lower rank. The actions, attitudes, and relationships of the dominant and subordinate individuals constitute components of role behavior that can vary widely in form, style, and content, but do not vary in the expectation of obedience by the one of superior status, and willingness to obey from the subordinate. Authority is highly influential on the formal structure of the organization, including patterns of communication, sanctions, and rewards, as well as on the establishment of goals, objectives, and values of the organization.
Decisions can be complex admixtures of facts and values. Information about facts, especially empirically proven facts or facts derived from specialized experience, are more easily transmitted in the exercise of authority than are the expressions of values. Simon is primarily interested in seeking identification of the individual employee with the organizational goals and values. Following Lasswell[17] he states that “a person identifies himself with a group when, in making a decision, he evaluates the several alternatives of choice in terms of their consequences for the specified group”.[18] A person may identify himself with any number of social, geographic, economic, racial, religious, familial, educational, gender, political, and sports groups. Indeed, the number and variety are unlimited. The fundamental problem for organizations is to recognize that personal and group identifications can either facilitate or obstruct correct decision making for the organization. A specific organization has to deliberately determine and specify in appropriate detail and clear language its own goals, objectives, means, ends, and values.
Chester Barnard pointed out that “the decisions that an individual makes as a member of an organization are quite distinct from his personal decisions”.[19] Personal choices may determine whether an individual joins a particular organization, and continue to be made in his or her extra–organizational private life. But, as a member of an organization, that individual makes decisions not in relationship to personal needs and results, but in an impersonal sense as part of the organizational intent, purpose, and effect. Organizational inducements, rewards, and sanctions are all designed to form, strengthen, and maintain this identification.
The correctness of decisions is measured by two major criteria:
  • adequacy of achieving the desired objective; and
  • the efficiency with which the result was obtained. Many members of the organization may focus on adequacy, but the overall administrative management must pay particular attention to the efficiency with which the desired result was obtained.
Simon's contributions to research in the area of decision-making have become increasingly mainstream in the business community thanks to the growth of management consulting.
[edit] Contributions to artificial intelligenceSimon was a pioneer in the field of artificial intelligence, creating with Allen Newell the Logic Theory Machine (1956) and the General Problem Solver (GPS) (1957) programs. GPS was possibly the first method of separating problem solving strategy from information about particular problems. Both programs were developed using the Information Processing Language (IPL) (1956) developed by Newell, Cliff Shaw and Simon. Donald Knuth mentions the development of list processing in IPL with the linked list originally called "NSS memory" for its inventors.[20] In 1957, Simon predicted that computer chess would surpass human chess abilities within "10 years" when, in reality, that transition took about 40 years.[21]
In the early 1960s Simon wrote a paper responding to a claim by the psychologist Ulric Neisser that machines might be able to replicate 'cold cognition', e.g. processes like reasoning, planning, perceiving, and deciding, but could not replicate 'hot cognition', including desiring, feeling pain or pleasure, and having emotions. Simon's paper was eventually published in 1967.[22] It was ignored by the AI research community for some years, but later became very influential e.g. indirectly through the work of Sloman and Picard on emotions.
Simon also collaborated with James G. March on several works in organization theory.
With Allen Newell, Simon developed a theory for the simulation of human problem solving behavior using production rules.[23] The study of human problem solving required new kinds of human measurements and, with Anders Ericsson, Simon developed the experimental technique of verbal protocol analysis.[24] Simon was interested in the role of knowledge in expertise. He said that to become an expert required about 10 years of experience and he and colleagues estimated that expertise was the result of learning roughly 50,000 chunks of information. A chess expert was said to have learned about 50,000 chunks or chess position patterns.[25]
Simon was also interested in how humans learn and, with Edward Feigenbaum, he developed the EPAM (Elementary Perceiver and Memorizer) theory, one of the first theories of learning to be implemented as a computer program. EPAM was able to explain a large number of phenomena in the field of verbal learning.[26] Later versions of the model were applied to concept formation and the acquisition of expertise.
He was awarded ACM's A.M. Turing Award along with Allen Newell in 1975. "In joint scientific efforts extending over twenty years, initially in collaboration with J. C. (Cliff) Shaw at the RAND Corporation, and subsequentially with numerous faculty and student colleagues at Carnegie Mellon University, they have made basic contributions to artificial intelligence, the psychology of human cognition, and list processing."
[edit] Contributions to sociology and economicsHerbert Simon has been credited for revolutionary changes in microeconomics. He is responsible for the concept of organizational decision-making as it is known today. He was also the first to discuss this concept in terms of uncertainty; i.e. it is impossible to have perfect and complete information at any given time to make a decision. While this notion was not entirely new, Simon is best known for its origination. It was in this area that he was awarded the Nobel Prize in 1978.
At the Cowles Commission, Simon’s main goal was to link economic theory to mathematics and statistics. His main contributions were to the fields of general equilibrium and econometrics. He was greatly influenced by the marginalist debate that began in the 1930s. The popular work of the time argued that it was not empirically apparent that entrepreneurs needed to follow the marginalist principles of profit-maximization/cost-minimization in running organizations. The argument went on to note that profit-maximization was not accomplished, in part, because of the lack of complete information. In decision-making, Simon believed that agents face uncertainty about the future and costs in acquiring information in the present. These factors limit the extent to which agents can make a fully rational decision, thus they possess only “bounded rationality” and must make decisions by “satisficing,” or choosing that which might not be optimal but which will make them happy enough.
Simon was known for his research on industrial organization. He determined that the internal organization of firms and the external business decisions thereof did not conform to the Neoclassical theories of “rational” decision-making. Simon wrote many articles on the topic over the course of his life mainly focusing on the issue of decision-making within the behavior of what he termed “bounded rationality”. “Rational behavior, in economics, means that individuals maximizes his utility function under the constraints they face (e.g., their budget constraint, limited choices, ...) in pursuit of their self-interest. This is reflected in the theory of subjective expected utility. The term bounded rationality is used to designate rational choice that takes into account the cognitive limitations of both knowledge and cognitive capacity. Bounded rationality is a central theme in behavioral economics. It is concerned with the ways in which the actual decision-making process influences decisions. Theories of bounded rationality relax one or more assumptions of standard expected utility theory”.
Simon determined that the best way to study these areas was through computer simulation modeling. As such, he developed an interest in computer science. Herbert Simon's main interests in computer science were in artificial intelligence, human-computer interaction, principles of the organization of humans and machines as information processing systems, the use of computers to study (by modeling) philosophical problems of the nature of intelligence and of epistemology, and the social implications of computer technology. Some of Simon's economic research was directed toward understanding technological change in general and the information processing revolution in particular.
While living in Pittsburgh, PA, he advised the citizenry on various issues including the use of public funds to build stadiums and the method of raising tax revenue. Simon emphasized the usefulness of the land tax, reflecting the early influence of Henry George on his economic thought.
[edit] Contributions to pedagogySimon's work has strongly influenced John Mighton, developer of a remedial program which has achieved significant success in improving mathematics performance among elementary and high school students.[27] Mighton cites a 2000 paper by Simon and two co-authors which counters arguments by French mathematics educator Guy Brousseau and others suggesting that excessive practice hampers children's understanding:[27]
[The] criticism of practice (called 'drill and kill,' as if this phrase constituted empirical evaluation) is prominent in constructivist writings. Nothing flies more in the face of the last 20 years of research than the assertion that practice is bad. All evidence, from the laboratory and from extensive case studies of professionals, indicates that real competence only comes with extensive practice.... In denying the critical role of practice one is denying children the very thing they need to achieve real competence. The instructional task is not to 'kill' motivation by demanding drill, but to find tasks that provide practice while at the same time sustaining interest.
— John R. Anderson, Lynne M. Reder, and Herbert A. Simon, 'Applications and misapplications
of cognitive psychology to mathematics education
', Texas Educational Review 6 (2000)
[edit] Contributions to library scienceSatisficing, as defined by Simon, can be applied to library and information science where researchers assess how much information is adequate to meet their information need. With the huge volume of information today, library researchers are forced to use Simon's model of satisficing when searching. The first satisfactory alternative is chosen over the best. Applying satisficing to research is a way for researchers to adjust to the vast amount of information today.[28]


Allen Newell                                                                                                                                        From Wikipedia, the free encyclopedia
                                                                                                                                                                                                                                                                                                                                                                                                                               

This article should be divided into sections by topic, to make it more accessible. Please help by adding section headings in accordance with Wikipedia's style guidelines. (October 2009)
Allen Newell
Born
March 19, 1927
San Francisco
Died
July 19, 1992 (aged 65)
Pittsburgh
Fields
Computer Science
Cognitive Psychology
Institutions
Carnegie Mellon University
Stanford University
Princeton University
Carnegie Mellon University
Herbert Simon
Known for
Information Processing Language
Soar
Notable awards
A.M. Turing Award (1975)
National Medal of Science (1992)
Louis E. Levy Medal (1992)
Allen Newell (March 19, 1927 – July 19, 1992) was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department of Psychology. He contributed to the Information Processing Language (1956) and two of the earliest AI programs, the Logic Theory Machine (1956) and the General Problem Solver (1957) (with Herbert Simon). He was awarded the ACM's A.M. Turing Award along with Herbert Simon in 1975 for their basic contributions to artificial intelligence and the psychology of human cognition.[1][2]
Contents [hide]
[edit] LifeNewell completed his Bachelor's degree from Stanford in 1949. He was a graduate student at Princeton University during 1949-1950 when he studied mathematics. Due to his early exposure to a new field known as game theory and the experiences from the study of mathematics, he was convinced that he would prefer "a combination of experimental and theoretical research to pure mathematics" (Simon). Soon after, he left Princeton and joined the RAND Corporation in Santa Monica where he worked for "a group that was studying logistics problems of the Air Force" (Simon). His work with Joseph Kruskal led to the creation of two theories: A Model for Organization Theory and Formulating Precise Concepts in Organization Theory. Newell eventually earned his PhD from the now Tepper School of Business at Carnegie Mellon with Herbert Simon serving as his advisor.
Afterwards, Newell "turned to the design and conduct of laboratory experiments on decision making in small groups" (Simon). He was dissatisfied, however, with the accuracy and validity of their findings produced from small-scale laboratory experiments. He joined with fellow RAND teammates John Kennedy, Bob Chapman, and Bill Biel at an Air Force Early Warning Station to study organizational processes in flight crews. They received funding from the Air Force in 1952 to build a simulator that would enable them to examine and analyze the interactions in the cockpit related to decision-making and information-handling. From these studies, Newell came to believe that information processing is the central activity in organizations.
In September 1954, Newell enrolled in a seminar where Oliver Selfridge "described a running computer program that learned to recognize letters and other patterns" (Simon). This was when Allen came to believe that systems may be created and contain intelligence and have the ability to adapt. With this in mind, Allen, after a couple months, wrote in 1955 The Chess Machine: An Example of Dealing with a Complex Task by Adaptation, which "outlined an imaginative design for a computer program to play chess in humanoid fashion" (Simon).
His work came to the attention of economist (and future nobel laureate) Herbert Simon, and, together with programmer J. C. Shaw, they developed the first true artificial intelligence program, the Logic Theorist. Newell's work on the program laid the foundations of the field. His inventions included: list processing, the most important programming paradigm used by AI ever since; the application of means-ends analysis to general reasoning (or "reasoning as search"); and the use of heuristics to limit the search space.
They presented the program at the Dartmouth conference of 1956, an informal gathering of researchers who were interested in simulating intelligence with machines. The conference, now widely considered the "birth of artificial intelligence",[3] was enormously influential and those who attended became the leaders of AI research for the next two decades, Newell included.
Newell and Simon formed a lasting partnership. They founded an artificial intelligence laboratory at Carnegie Mellon University and produced a series of important programs and theoretical insights throughout the late fifties and sixties. This work included the General Problem Solver, a highly influential implementation of means-ends analysis, and the physical symbol systems hypothesis, the controversial philosophical assertion that all intelligent behavior could be reduced to the kind of symbol manipulation that Newell's programs demonstrated.
Newell's work culminated in the development of a cognitive architecture known as Soar and his unified theory of cognition, published in 1990, but their improvement was the objective of his efforts up to his death (one of the last Newell's letters).
[edit] Awards and honorsThe Award for Research Excellence of the Carnegie Mellon School of Computer Science was named in his honor.

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发表于 2011-9-6 23:58:32 | 显示全部楼层
提示: 作者被禁止或删除 内容自动屏蔽
发表于 2011-9-17 17:04:59 | 显示全部楼层
顶一个~~  想问一下楼主,如何去读一个引擎里面的AI部分呢?

就是想基于引擎的AI系统来开发更丰富,更棒的AI~~  谢谢~~
 楼主| 发表于 2011-9-17 23:22:37 | 显示全部楼层
HeeZee 发表于 2011-9-17 17:04
顶一个~~  想问一下楼主,如何去读一个引擎里面的AI部分呢?

就是想基于引擎的AI系统来开发更丰富,更棒的 ...

呵呵,这个问题很难说。如果只是想做开发呢,这个首先你最好比较一下引擎之间的优缺点,选择一款你觉得比较适合你的引擎。然后认认真真读一些demo,自己动手实现一些例子。
发表于 2011-9-28 09:52:31 | 显示全部楼层
现在是刀耕火种的洪荒时代。什么全部自己动手写的
 楼主| 发表于 2011-9-28 10:55:58 | 显示全部楼层
wotacid 发表于 2011-9-28 09:52
现在是刀耕火种的洪荒时代。什么全部自己动手写的

呵呵,有句话叫做站在巨人的肩膀上,有能力,你也可以站一下。
发表于 2011-9-28 18:53:24 | 显示全部楼层
我是要做巨人的,这个只能免了
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