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Decision analysis: a Bayesian approach

Classics

Chapman and Hall. See also: Influence diagrams for Bayesian decision analysis, European Journal of Operational Research, Volume 40, Issue 3, 15 June 1989, Pages 363–376 (http://www.sciencedirect.com/science/article/pii/0377221789904293). Bayesian Decision Analysis: Principles and Practice, Cambridge University Press, 2010 (https://books.google.com/books/about/Bayesian_Decision_Analysis.html?id=O1lXnQAACAAJ).




A Simple View of the Dempster-Shafer Theory of Evidence and Its Implication for the Rule of Combination

AI Magazine

During the past two years, the Dempster-Shafer theory of evidence has attracted considerable attention within the AI community as a promising method of dealing with uncertainty in expert systems. As presented in the literature, the theory is hard to master. In a simple approach that is outlined in this paper, the Dempster-Shafer theory is viewed in the context of relational databases as the application of familiar retrieval techniques to second-order relations in first normal form. The relational viewpoint clarifies some of the controversial issues in the Dempster-Shafer theory and facilities its use in AI-oriented applications.


Review of Artificial Intelligence and Robotics: Five Overviews

AI Magazine

AI Magazine Volume 7 Number 1 (1986) ( AAAI) of the crucial terms involved in his analysis, such as "probability" Mauadne 4(4):7-14 falsity of his claims is often impossible to assess. Nute, Donald k. '(1980) Topics in conditional logic Dordrecht, Holland: conceptions upon which his view is based do indeed conform M. Ringle, (Ed.), Philosophical Perspectives in Artificial Intelligence traditional conceptions should not be taken for granted, Terry L. Rankin his observation that "Probability theory is today our primary At hens, Georgia such as "average" and "likely," and therefore it is the most natural language for describing those aspects of (heuristic) performance that we seek to improve" (p. Artificial Intelligence and Robotics: On general theoretical grounds, I think, there are excellent Five Overviews. Busi-reasons to suppose that (a)-(f) are fundamental ness/Technology Books; 1984. Gevarter's work was published by the National that serious difficulties seem to confront the theoretical Bureau of Standards as a set of five volumes, and this book, framework he apparently endorses, where these difficulties published by Business/Technology Books, is Gevarter's are especially severe from an epistemological perspective.


The Advanced Computational Methods Center, University of Georgia

AI Magazine

The Advanced Computational Methods Center (ACMC) established at the University of Georgia in 1984, supports several research projects in artificial intelligence. The primary goal of AI research at ACMC is the design and installation of a logic-programming environment with advanced natural language processing and knowledge-acquisition capabilities on the university's highly parallel CYBERPLUS system from Control Data Corporation. This article briefly describes current research projects in artificial intelligence at ACMC


The Next Knowledge Medium

AI Magazine

Public opinion about artificial intelligence is schizophrenic. "It will never work" versus "It might cost me changes that are daily taking place in the This dichotomy of attitudes reflects a collective world because we read about them and know confusion about AI.


Induction of decision trees

Classics

The technology for building knowledge-based systems by inductive inference from examples hasbeen demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directionsMachine Learning, 1, p. 81-106


Artificial Intelligence Research in France

AI Magazine

In the first section, some characteristic features of AI research in France are presented, including difficulties with the current means and the current organization of AI research. In the second section, the state-of-the-art in different areas of AI is described. Besides some weakness, and in spite of the general difficulties mentioned in the first section, strong points and great potentialities are exhibited. This allows us to conclude that AI research in France may play an important part at the international level, if the necessary means for its development in the middle and long term are given.


Knowledge and Experience in Artificial Intelligence

AI Magazine

The period since the last conference in this series has been characterized by the explosive expansion of AI out of the confines of institutions of basic research like university departments into the worlds of industry, business, and government (a development I had long expected). But it seems to me that there are plenty -- perhaps an overabundance -- of other occasions, other conferences. Other workshops, and like, at which the applications of AI would appropriately be considered. I will confine my remarks, therefore, to issues of basic research.