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Mathematical psychology is an approach to psychological research that is based on mathematical modeling of perceptual, thought, cognitive and motor processes, and on the establishment of law-like rules that relate quantifiable stimulus characteristics with quantifiable behavior (in practice often constituted by task performance).
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The theory of conjoint measurement (also known as conjoint measurement or additive conjoint measurement) is a general, formal theory of continuous quantity.It was independently discovered by the French economist Gérard Debreu (1960) and by the American mathematical psychologist R. Duncan Luce and statistician John Tukey (Luce & Tukey 1964).
The Journal of Mathematical Psychology is a peer-reviewed scientific journal established in 1964. It covers all areas of mathematical and theoretical psychology, including sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation.
Robert Duncan Luce (May 16, 1925 – August 11, 2012) [1] was an American mathematician and social scientist, and one of the most preeminent figures in the field of mathematical psychology. At the end of his life, he held the position of Distinguished Research Professor of Cognitive Science at the University of California, Irvine .
Clyde Hamilton Coombs (July 22, 1912 – February 4, 1988) was an American psychologist specializing in the field of mathematical psychology. [1] He devised a voting system, that was hence named Coombs' method. Coombs founded the Mathematical Psychology program at the University of Michigan.
The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology. Cambridge, MA and London: The MIT Press. ISBN 9780262062121. OCLC 43109956. Fodor, Jerry (2010). LOT 2: The Language of Thought Revisited. Oxford and New York: Oxford University Press. ISBN 9780199548774. OCLC 470698989. Harnad, Stevan (1994). "Computation Is Just ...
Mathematical modeling is useful in developmental psychology for implementing theory in a precise and easy-to-study manner, allowing generation, explanation, integration, and prediction of diverse phenomena. Several modeling techniques are applied to development: symbolic, connectionist (neural network), or dynamical systems models.