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Author:   Darlene Crone-Todd ,  Donald A. Hantula (Temple University, USA) ,  T. V. Joe Layng (Endicott College, Massachusetts, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   Routledge
Weight:   0.480kg
ISBN:  

9781032462172

ISBN 10:   1032462175
Pages:   172
Publication Date:   17 March 2026
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Section 1: Foundations of Digital Technology and Behavioral Science 1. Technology and Computer Programming in Behavior Analysis: Historical Trends and Guidance for Behavior Analysts 2. Complex Systems Theory in Behavior Analysis 3. Behavioral Science in the Fourth Industrial Revolution; Section 2: Machine Learning, AI, and Predictive Models in Behavior Science 4. Machine Learning to Support Decision-Making in Behavior Analysis: Current Research and Future Directions 5. Reinforcement Learning in Behavior Science and Artificial Intelligence 6. Extending Neural Network Predictions of Human Behaviors; Section 3: Tools and Technologies for Research and Applications 7. An Updated and Simplified Version of a Low-Cost Arduino-Visual Basic Interface for Operant Research 8. Simulation-Based Assessment and Training 9. Using Virtual Reality within Behavior Analysis Practice 10. Behavioral and Digital Technologies in the Treatment of Substance Use Disorder 11. Developing AI Personas for Use in Behavior Analytic Training: A Case Study of an Autism Parent

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Author Information

Darlene E. Crone-Todd is Professor Emeritus in the Department of Psychology at Salem State University, USA. Donald A. Hantula is Associate Professor at the Department of Psychology and Neuroscience, College of Liberal Arts, Temple University. USA. T.V. Joe Layng is Adjunct Professor of Behavior Analysis, Endicott College, USA. He is also Co-founder and Partner of Generategy, an educational software company whose products are based on generative instruction principles.

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