William K. Estes

William Kaye Estes (b.1919) is an American scholar in the field of psychological and brain sciences, with his most substantial contributions made in mathematical learning theory.

Estes obtained his B.A. in psychology in 1940 and a Ph.D. in psychology in 1943 from the University of Minnesota. He started his academic career at the Indiana University in 1946, where he became Research Professor in 1960. Two years later he moved on to teach at Stanford University, then in 1968 he moved to Rockefeller University and in 1979 to Harvard University. In 1999, he came back to Indiana University as Distinguished Scholar in the Department of Psychology and in the Cognitive Science Program.

Estes has received numerous awards, such as the Distinguished Research Contribution Award of the American Psychological Association (1962), the American Psychological Foundation Gold Medal for Lifetime Achievement in Psychological Science (1992) and the US National Medal of Science (1997). He has obtained honorary Doctor of Science degrees from Indiana University and the University of Minnesota. Among Estes's seminal works are Learning Theory and Mental Development (1970), Statistical Models in Behavioral Research (1991), and Classification and Cognition (1994).

The early work of Estes was heavily influenced by the teachings of American behavioral psychologist Burrhus Frederic Skinner (1904 1990) and was focused on animal learning and behavior. Both scholars worked on the problem of instrumental learning and emotions and developed a method of measuring of the so-called conditioned emotional response (CER). In the 1960s, Estes shifted his attention to studying visual information processing and contributed to the development of a method of estimating the information perceived from brief visual displays. Later works of the scientist focus on mathematical and computer models of human memory and classification learning.

Estes has been credited for being a founder of modern mathematical psychology, mainly due to the stimulus sampling theory (SST) which he introduced in the 1950s as a model of description of learning situations via mathematical means. Estes developed the SST as his contribution to contemporary approaches to learning that described the learning situation as combination of stimulus, response and reinforcement. In these theories, the stimulus usually refers to the environmental situation, regarding to which the subject's behavior is observed. The response covers all observable behaviors that change in some orderly manner during learning, while reinforcement is considered as the experimental operations or events deemed crucial for learning production.

In his research, Estes used mathematical sets to represent certain aspects of the stimulus situation. Thus, he joined the tradition of a discipline named mathematical learning theory, which is perhaps best known for the influential works of Clark Leonard Hull (1884-1952) and Kenneth W. Spence (1907-1967). Generally, the mathematical learning theory covers a group of research methods and results related to the conceptual representation of learning phenomena, the formulation of assumptions or hypotheses about learning in mathematical therms, in addition to the derivation of testable theorems.

Estes believed that following the application of mathematical terminology to a learning situation, the whole environment becomes a population of discrete stimulus elements, while the stimuli that affect the learning subject become a sample of this population. Therefore, the stimulus-sampling models, which Estes also calls statistical learning models, are models of the stimulus environment of an experimental subject and of the processes by which that environment influences behavior.

A general assumption of the SST is that the subject draws a sample of the population on each trial of a learning experiment. In tune with stimulus-response theories, the SST also postulates that the stimuli are connected or conditioned to different responses of the subject. The SST adopts two major axioms. The first is that response probabilities are related to the proportion of conditioned elements in a sample. The second axiom specifies how these conditioned elements change their state of conditioning as different events happen. Thus the SST is interested in how response probabilities are transformed from one trial to another.

The general stimulus-sampling approach has been applied to different, more specific, experimental problems. For example, this approach has been used to study the problem of mediated generalization - a type of behavior which involves the similar treatment of two stimuli not because they are physically alike but because they are associated with a third, common stimulus. This approach has also been used to research "vicarious trial and error" (VTE) behavior - the hesitant reactions a person displays before making a choice, especially when it comes to choosing directions.

William K. Estes: Selected full-text books and articles

Statistical Models in Behavioral Research By William K. Estes Lawrence Erlbaum Associates, 1991
Cognition in Human Motivation and Learning By Gery D'Ydewalle; Willy Lens Leuven University Press; Lawrence Erlbaum Associates, 1981
Librarian's tip: Chap. 6 "Cognitive Processes in Reinforcement and Choice" by W. K. Estes
Mechanisms of Learning and Motivation: A Memorial Volume to Jerzy Konorski By Anthony Dickinson; Robert A. Boakes Lawrence Erlbaum Associates, 1979
Librarian's tip: Chap. 16 "Cognitive Processes in Conditioning" by W. K. Estes
Foundations for a Psychology of Education By Alan Lesgold; Robert Glaser Lawrence Erlbaum Associates, 1989
Librarian's tip: "Learning Theory" by W. K. Estes begins on p. 1
Readings in Learning By Lawrence M. Stolurow Prentice-Hall, 1953
Librarian's tip: "Toward a Statistical Theory of Learning" by William K. Estes begins on p. 44 and "Motivation in Secondary Reinforcement" by William K. Estes begins on p. 166
Memory and Learning: The Ebbinghaus Centennial Conference By David S. Gorfein; Robert R. Hoffman Lawrence Erlbaum Associates, 1987
Librarian's tip: Chap. 2 "One Hundred Years of Memory Theory" by William K. Estes
Studies in Mathematical Learning Theory By Robert R. Bush; William K. Estes Stanford University Press, 1959
Librarian's tip: Chap. 1 "Component and Pattern Models with Markovian Interpretations" by William K. Estes and Chap. 8 "Foundations of Linear Models" by William K. Estes
Current Trends in Psychological Theory: A Bicentennial Program By Wayne Dennis; Dorwin Cartwright; E. Lowell Kelly; Alan E. Fisher; Mark R. Rosenzweig; David Krech; Edward L. Bennett; Peter M. Milner; William K. Estes; Allen Newell; Herbert A. Simon; Howard H. Kendler; O. Hobart Mowrer; B. F. Skinner University of Pittsburgh Press, 1961
Librarian's tip: "Growth and Function of Mathematical Models for Learning" by William K. Estes begins on p. 134
The Matching Principle Revisited By Green, Edward J.; Kemeny, John The Psychological Record, Vol. 52, No. 3, Summer 2002
Peer-reviewed publications on Questia are publications containing articles which were subject to evaluation for accuracy and substance by professional peers of the article's author(s).
Discourse Comprehension: Essays in Honor of Walter Kintsch By Walter Kintsch; Charles A. Weaver III; Suzanne Mannes; Charles R. Fletcher Lawrence Erlbaum Associates, 1995
Librarian's tip: Chap. 3 "A General Model of Classification and Memory Applied to Discourse Processing" by W. K. Estes
Choice, Decision, and Measurement: Essays in Honor of R. Duncan Luce By R. Duncan Luce; A. A. J. Marley Lawrence Erlbaum Associates, 1997
Librarian's tip: "Some Reflections on the Role of the Choice Model in Theories of Categorization, Identification, and Learning" by W. K. Estes
Decision Processes By Robert McDowell Thrall; C. H. Coombs; R. L. Davis Wiley, 1954
Librarian's tip: Chap. IX "Individual Behavior in Uncertain Situations: An Interpretation in Terms of Statistical Association Theory" by W. K. Estes
Sources of Coherence in Reading By Robert F. Lorch Jr.; Edward J. O'Brien Lawrence Erlbaum Associates, 1995
Librarian's tip: Chap. 3 "Response Processes in Cognitive Models" by W. K. Estes
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