Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.

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  • AUT: Autism

    CBM: Clinical/Family/Behavioral Medicine

    CSE: Community Interventions, Social and Ethical Issues

    EAB: Experimental Analysis of Behavior

    EDC: Education

    OBM: Organizational Behavior Management

    PRA: Practice

    TBA: Teaching Behavior Analysis

    TPC: Theoretical, Philosophical, and Conceptual Issues

    VRB: Verbal Behavior

    NON: NONE

2012 Theory and Philosophy Conference

Event Details


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Invited Symposium #7
CE Offered: PSY/BACB
Patterns of Explanation in Behavior Analysis: Models and Theories
Sunday, November 4, 2012
11:00 AM–1:30 PM
Zuni Ballroom
Area: TPC; Domain: Theory
Discussant: John W. Donahoe (University of Massachusetts, Amherst)
CE Instructor: John W. Donahoe, Ph.D.
Abstract:

Patterns of Explanation in Behavior Analysis: Models and Theories

 
Theories of Learning Are Necessary
PETER KILLEEN (Arizona State University)
Abstract: Skinner's famous article, "Are Theories of Learning Necessary?" was provocative and elliptical. The answer to his title becomes obvious when the ellipses are resolved: ... Necessary for a Science of Behavior? His own life work, in particular his three-term contingency, provided an important start on such a theory. In this talk, Skinner's work is embedded in the Aristotlean causal framework that stipulates the four questions we must answer for a complete explanation—for a complete theory—of a phenomenon; and the fifth that is entailed in the case of a dynamic process such as learning. Skinner provided two of those answers, and repudiated the others as wrong because they are extra-dimensional. This talk reasserts those questions and discusses the techniques that may be used to determine the adequacy with which provisional answers to the questions accord with the phenomenon under study. The approach is exemplified with the work of some of the participants of this conference.
Peter Killeen received his doctorate in 1969 under the furrowed brows of Howard Rachlin, Dick Herrnstein, and B. F. Skinner. He then absconded to Arizona State University—previously known as "Fort Skinner in the Desert." His research involved choice behavior, schedule-induced activities such as polydipsia, models of reinforcement schedules, timing, and delay discounting (additive utility model). He has received numerous reinforcers including the Woodrow Wilson Graduate Fellowship, Graduate Student Faculty of the Year, the Poetry in Science Award, and the F. J. McGuigan Lectureship on Understanding the Human Mind. He also served as a resident of the Society of Experimental Psychologists, the Society for the Quantitative Analysis of Behavior, and of the third International Seminar on Behavior. He received the Hilgard Award for the Best Theoretical Paper on Hypnosis and was featured on the "Faculty of 1,000" website (www.f1000.com) for a paper on attention deficit hyperactivity disorder. Additionally, he was covered in the "Emerging Research Front" feature on Thomson Reuters Sciencewatch for his work in inferential statistics (statistical hypothesis inference tests). Retired from teaching and administration, he continues his research on tobacco addiction, ADHD, and schedule effects and continues to mentor graduate students. He enjoys hiking in the desert mountains and admiring his grandkids.
 

Complexity Theories in Behavior Analysis

JACK J. MCDOWELL (Emory University)
Abstract:

A complexity theory is stated as a set of relatively simple rules that operate repeatedly to generate an output. The output, which typically exhibits properties and features that are not immediately derivable from the rules themselves, is then compared to the natural phenomena the theory purports to explain. At least four instances of complexity theory have appeared in behavior analysis. These are Charles P. Shimp's theory of momentary maximizing, John Donahoe and colleagues' theory of neural networks, A. Charles Catantia's theory of the reflex reserve, and Jack McDowell's theory of behavioral evolution. Each theory generates behavior by means of the rules it implements. If the generated behavior is comparable to the behavior of live organisms, then what is one warranted in asserting about the rules that constitute the theory? For example, is it important that they correspond to events and processes in the natural world? What is the nature of a theory that generates output that is consistent with observation, but that consists of rules that do not correspond, or cannot be determined to correspond, to events in the natural world? Answers to these questions may lead to a more or less maintainable distinction between a model and a theory, and to a profitable discussion of the relative value of these two types of account.

Jack J. McDowell received a BA from Yale University in 1972 and a Ph.D. from the State University of New York at Stony Brook in 1979. After completing his clinical internship, he joined the faculty of Emory University, where he currently serves as a professor in the Department of Psychology. Dr. McDowell also is a licensed clinical psychologist and maintains a private practice of behavior therapy in Atlanta, GA. His research has focused on the quantitative analysis of behavior. He has conducted tests of matching theory in experiments with humans, rats, and pigeons; has made formal mathematical contributions to the matching theory literature; and has proposed a computational theory of behavior dynamics. He also has written on the relevance of mathematical and computational accounts of behavior for the treatment of clinical problems. His current research is focused on his computational theory of selection by consequences, including studies of behavior generated by the theory's genetic algorithm and possible implementations of the theory in neural circuitry. His work, including collaborations with students and former students, has been funded by NIMH, NSF, and NIDA.
 

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