W. Todd Maddox

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About

W. Todd Maddox is a cognitive scientist whose research bridges human learning, artificial intelligence, and decision-making. His work explores how humans teach and interact with intelligent agents, with a focus on category learning, cognitive control, and the dynamics of human-machine collaboration. In his highly cited 2012 paper "How Humans Teach Agents" (85 citations), Maddox and his colleagues examined the strategies people use to instruct artificial agents, revealing critical insights into the alignment between human teaching behaviors and machine learning algorithms. This foundational work has influenced the design of interactive AI systems and human-robot teaching paradigms. Beyond this, Maddox has made significant contributions to understanding the neural and computational mechanisms underlying categorization and executive function, often integrating behavioral experiments with computational modeling. His research has been widely recognized, with multiple papers accumulating hundreds of citations, and he has served as a principal investigator on numerous National Science Foundation grants. For students and researchers, Maddox’s work offers a compelling lens into how cognitive science informs the development of more intuitive, human-centered artificial intelligence.