William Hayes leads the Decision Research and Modeling (DReaM) lab at 黑料视频. His research focuses on the cognitive processes involved in decision making and the role that context plays in shaping choice behavior. For example, people鈥檚 preferences can change dramatically depending on the set of available options or the way that choices are presented, but how can we explain these effects in terms of underlying cognitive processes? Another line of research examines the computational mechanisms that support experience-based decision-making. These studies primarily aim to develop and test models that describe how people encode the outcomes of past choices and either adapt or fail to adapt their behavior to maximize long-term rewards. The DReaM lab employs a variety of techniques to study these topics, including large-scale online experiments, process tracing methods (eye-tracking and mouse-tracking) and computational modeling. Accepting graduate students for Fall 2024. Representative Publications Hayes, W. M., Holmes, W. R., & Trueblood, J. S. (submitted). Attribute comparability and context effects in preferential choice. Trueblood, J. S., Liu, Y., Murrow, M., Hayes, W. M., & Holmes, W. R. (submitted). Attentional dynamics explain the elusive nature of context effects. Hayes, W. M., & Wedell, D. H. (2023). Effects of blocked versus interleaved training on relative value learning. Psychonomic Bulletin & Review. Online first publication. Hayes, W. M., & Wedell, D. H. (2023). Testing models of context-dependent outcome encoding in reinforcement learning. Cognition, 230, 105280. Hayes, W. M., & Wedell, D. H. (2022). Reinforcement learning in and out of context: The effects of attentional focus. Journal of Experimental Psychology: Learning, Memory, and Cognition. Online first publication. Hayes, W. M., & Wedell, D. H. (2021). Regret in experience-based decisions: The effects of expected value differences and mixed gains and losses. Decision, 8(4), 277-294.
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