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Individual choice behavior [electronic resource] : a theoretical analysis / R. Duncan Luce.

By: Luce, R. Duncan (Robert Duncan).
Publisher: Mineola, N.Y. : Dover Publications, 2005Description: xii, 153 p. : ill. ; 22 cm.ISBN: 0486441369 (electronic bk.); 9780486441368 (electronic bk.).Subject(s): Psychometrics | Choice (Psychology) | Psychometrics | Choice BehaviorAdditional physical formats: OriginalDDC classification: 153.8/3 Online resources: Fulltext available via EBSCOhost - Shibboleth login required Also issued in print.Summary: "Aside from statistics, the most extensive and systematic mathematical applications in psychology have so far centered about problems of organisms making choices from discrete, well-defined sets of alternatives. One need only recall that this is a feature common to information theory, much of psychophysical scaling, utility theory and decision theory generally, stochastic learning theory, and many of the psychometric models. Whether it is a deep or superficial feature is another matter, but there can be little doubt that it exists. If it is deep, one can anticipate considerable benefit accruing to its exposure and study; if not, the study should make clearer some of the inherent differences that have led to a variety of theories. The purpose of this book is to undertake such a study. A simple probabilistic theory is presented that overlaps each of these fields in a significant way. It by no means subsumes them, but it does seem to be central in part of the development of each. To this common theory each special topic adds conditions of its own that result in its distinctive quality. The book is theoretical in the sense that it offers a mathematical theory of choice behavior, and it is not empirical in the sense that no new data are presented. It is not, however, anti-empirical. Throughout, questions of empirical verification are considered, and, wherever possible, existing data have been brought to bear. Whether the theory will ultimately have serious empirical consequences remains to be seen, but at the least it has initiated a number of experimental studies which will be reported in the periodical literature"--Preface.Summary: "This Influential treatise presents upper-level undergraduates and graduate students with a mathematical analysis of choice behavior. It begins with the statement of a general axiom upon which the rest of the book rests; the following three chapters, which may be read independently of each other, are devoted to applications of the theory to substantive problems: psychophysics, utility, and learning. Applications to psychophysics include considerations of time- and space-order effects, the Fechnerian assumption, the power law and its relation to discrimination data, interaction of continua, discrimined processes, signal detectability theory, and rethinking of stimulus. The next major theme, utility theory, features unusual results that suggest an experiment to test the theory. The fined chapters explore learning-related topics, analyzing the stochastic theories of learning as the basic approach--with the exception that distributions of response strengths are assumed to be transformed rather than response probabilities. The author arrives at three classes of learning operators, both linear and nonlinear, and the text concludes with a useful series of appendixes"--Cover. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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Originally published: New York : Wiley, 1959.

Includes bibliographical references (p. 147-149) and index.

"Aside from statistics, the most extensive and systematic mathematical applications in psychology have so far centered about problems of organisms making choices from discrete, well-defined sets of alternatives. One need only recall that this is a feature common to information theory, much of psychophysical scaling, utility theory and decision theory generally, stochastic learning theory, and many of the psychometric models. Whether it is a deep or superficial feature is another matter, but there can be little doubt that it exists. If it is deep, one can anticipate considerable benefit accruing to its exposure and study; if not, the study should make clearer some of the inherent differences that have led to a variety of theories. The purpose of this book is to undertake such a study. A simple probabilistic theory is presented that overlaps each of these fields in a significant way. It by no means subsumes them, but it does seem to be central in part of the development of each. To this common theory each special topic adds conditions of its own that result in its distinctive quality. The book is theoretical in the sense that it offers a mathematical theory of choice behavior, and it is not empirical in the sense that no new data are presented. It is not, however, anti-empirical. Throughout, questions of empirical verification are considered, and, wherever possible, existing data have been brought to bear. Whether the theory will ultimately have serious empirical consequences remains to be seen, but at the least it has initiated a number of experimental studies which will be reported in the periodical literature"--Preface.

"This Influential treatise presents upper-level undergraduates and graduate students with a mathematical analysis of choice behavior. It begins with the statement of a general axiom upon which the rest of the book rests; the following three chapters, which may be read independently of each other, are devoted to applications of the theory to substantive problems: psychophysics, utility, and learning. Applications to psychophysics include considerations of time- and space-order effects, the Fechnerian assumption, the power law and its relation to discrimination data, interaction of continua, discrimined processes, signal detectability theory, and rethinking of stimulus. The next major theme, utility theory, features unusual results that suggest an experiment to test the theory. The fined chapters explore learning-related topics, analyzing the stochastic theories of learning as the basic approach--with the exception that distributions of response strengths are assumed to be transformed rather than response probabilities. The author arrives at three classes of learning operators, both linear and nonlinear, and the text concludes with a useful series of appendixes"--Cover. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Also issued in print.

Electronic reproduction. Washington, D.C. : American Psychological Association, 2014. Available via World Wide Web. Access limited by licensing agreement. s2014 dcunns

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