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  1. Resource Rationality.Thomas F. Icard - manuscript
    Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for normative assessment (...)
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  • Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    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 computational mechanism into the definition of (...)
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  • Dividing Attention Between Tasks: Testing Whether Explicit Payoff Functions Elicit Optimal Dual-Task Performance.George D. Farmer, Christian P. Janssen, Anh T. Nguyen & Duncan P. Brumby - 2018 - Cognitive Science 42 (3):820-849.
    We test people's ability to optimize performance across two concurrent tasks. Participants performed a number entry task while controlling a randomly moving cursor with a joystick. Participants received explicit feedback on their performance on these tasks in the form of a single combined score. This payoff function was varied between conditions to change the value of one task relative to the other. We found that participants adapted their strategy for interleaving the two tasks, by varying how long they spent on (...)
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  • Modeling task effects in human reading with neural network-based attention.Michael Hahn & Frank Keller - 2023 - Cognition 230 (C):105289.
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  • Now or … later: Perceptual data are not immediately forgotten during language processing.Klinton Bicknell, T. Florian Jaeger & Michael K. Tanenhaus - 2016 - Behavioral and Brain Sciences 39.
    Christiansen & Chater propose that language comprehenders must immediately compress perceptual data by “chunking” them into higher-level categories. Effective language understanding, however, requires maintaining perceptual information long enough to integrate it with downstream cues. Indeed, recent results suggest comprehenders do this. Although cognitive systems are undoubtedly limited, frameworks that do not take into account the tasks that these systems evolved to solve risk missing important insights.
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  • Task effects reveal cognitive flexibility responding to frequency and predictability: Evidence from eye movements in reading and proofreading.Elizabeth R. Schotter, Klinton Bicknell, Ian Howard, Roger Levy & Keith Rayner - 2014 - Cognition 131 (1):1-27.
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