Optimality and some of its discontents: Successes and shortcomings of existing models for binary decisions

Philip Holmes, Jonathan D. Cohen

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

We review how leaky competing accumulators (LCAs) can be used to model decision making in two-alternative, forced-choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed-accuracy trade-off that optimizes reward rate for a restricted class of two alternative forced-choice decision tasks. We review findings that compare human performance with this benchmark, and we reveal both approximations to and deviations from optimality. We then discuss three potential sources of deviations from optimality at the psychological level-avoidance of errors, poor time estimation, and minimization of the cost of control-and review recent theoretical and empirical findings that address these possibilities. We also discuss the role of cognitive control in changing environments and in modulating exploitation and exploration. Finally, we consider physiological factors in which nonlinear dynamics may also contribute to deviations from optimality.

Original languageEnglish (US)
Pages (from-to)258-278
Number of pages21
JournalTopics in Cognitive Science
Volume6
Issue number2
DOIs
StatePublished - Apr 2014

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Human-Computer Interaction
  • Cognitive Neuroscience
  • Artificial Intelligence

Keywords

  • Accumulator
  • Cognitive control
  • Costs
  • Decision making
  • Drift-diffusion process
  • Exploitation
  • Exploration
  • Optimality
  • Robustness
  • Speed-accuracy trade-off

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