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Profile: Christopher Myers (University of Washington)
  1. Vladislav D. Veksler, Christopher W. Myers & Kevin A. Gluck (2014). SAwSu: An Integrated Model of Associative and Reinforcement Learning. Cognitive Science 38 (1):580-598.
    Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid-navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The (...)
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  2. Nancy J. Cooke, Jamie C. Gorman, Christopher W. Myers & Jasmine L. Duran (2013). Interactive Team Cognition. Cognitive Science 37 (2):255-285.
    Cognition in work teams has been predominantly understood and explained in terms of shared cognition with a focus on the similarity of static knowledge structures across individual team members. Inspired by the current zeitgeist in cognitive science, as well as by empirical data and pragmatic concerns, we offer an alternative theory of team cognition. Interactive Team Cognition (ITC) theory posits that (1) team cognition is an activity, not a property or a product; (2) team cognition should be measured and studied (...)
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  3. Wayne D. Gray, Michael J. Schoelles & Christopher W. Myers (2003). Meeting Newell's Other Challenge: Cognitive Architectures as the Basis for Cognitive Engineering. Behavioral and Brain Sciences 26 (5):609-610.
    We use the Newell Test as a basis for evaluating ACT-R as an effective architecture for cognitive engineering. Of the 12 functional criteria discussed by Anderson & Lebiere (A&L), we discuss the strengths and weaknesses of ACT-R on the six that we postulate are the most relevant to cognitive engineering.
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