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159The Adaptive Nature of Eye Movements in Linguistic Tasks: How Payoff and Architecture Shape Speed‐Accuracy Trade‐OffsTopics in Cognitive Science 5 (3): 581-610. 2013.We explore the idea that eye-movement strategies in reading are precisely adapted to the joint constraints of task structure, task payoff, and processing architecture. We present a model of saccadic control that separates a parametric control policy space from a parametric machine architecture, the latter based on a small set of assumptions derived from research on eye movements in reading (Engbert, Nuthmann, Richter, & Kliegl, 2005; Reichle, Warren, & McConnell, 2009). The eye-control model is …Read more
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85Utility Maximization and Bounds on Human Information ProcessingTopics in Cognitive Science 6 (2): 198-203. 2014.Utility maximization is a key element of a number of theoretical approaches to explaining human behavior. Among these approaches are rational analysis, ideal observer theory, and signal detection theory. While some examples of these approaches define the utility maximization problem with little reference to the bounds imposed by the organism, others start with, and emphasize approaches in which bounds imposed by the information processing architecture are considered as an explicit part of the ut…Read more
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72Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility MaximizationTopics in Cognitive Science 6 (2): 279-311. 2014.We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of co…Read more
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10Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learningArtificial Intelligence 112 (1-2): 181-211. 1999.
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7Risk-aware analysis for interpretations of probabilistic achievement and maintenance commitmentsArtificial Intelligence 317 (C): 103864. 2023.
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Fordham UniversityGraduate student
New York City, New York, United States of America