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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  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 . Finally, we show how the model recovers qualitative data patterns in another task of longstanding psychological interest, the AX Continuous Performance Test , using the same model parameters.|
|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|
|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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