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A Theory of Decision Making Under Dynamic Context

Author(s): Shvartsman, Michael; Srivastava, Vaibhav; Cohen, Jonathan D.

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Abstract: The dynamics of simple decisions are well understood and modeled as a class of random walk models [e.g. 1-4]. However, most real-life decisions include a dynamically-changing influence of additional information we call context. In this work, we describe a computational theory of decision making under dynamically shifting context. We show how the model generalizes the dominant existing model of fixed-context decision making [2] and can be built up from a weighted combination of fixed-context decisions evolving simultaneously. We also show how the model generalizes recent work on the control of attention in the Flanker task [5]. Finally, we show how the model recovers qualitative data patterns in another task of longstanding psychological interest, the AX Continuous Performance Test [6], using the same model parameters.
Publication Date: 1-Jan-2015
Citation: Shvartsman, M, Srivastava, V, Cohen, JD. (2015). A theory of decision making under dynamic context. Advances in Neural Information Processing Systems, 2015-January (2485 - 2493
ISSN: 1049-5258
Pages: 2485 - 2493
Type of Material: Conference Article
Journal/Proceeding Title: Advances in Neural Information Processing Systems
Version: Final published version. This is an open access article.

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