A theory of decision making under dynamic context

Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)2485-2493
Number of pages9
JournalAdvances in Neural Information Processing Systems
StatePublished - 2015
Event29th Annual Conference on Neural Information Processing Systems, NIPS 2015 - Montreal, Canada
Duration: Dec 7 2015Dec 12 2015

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing


Dive into the research topics of 'A theory of decision making under dynamic context'. Together they form a unique fingerprint.

Cite this