Behavioral Economics

  • Yakov Ben-Haim, 2006, Info-gap Decision Theory: Decisions Under Severe Uncertainty, 2nd edition, Academic Press, London.
    Chapter 11: Robust-Satisficing Behavior.
    … Section 11.1: The Ellsberg paradox.
    … Section 11.2: The Allais paradox.
    … Section 11.3: Info-gap analysis of expected-utility risk aversion.
    … Section 11.5: The equity premium puzzle: A solution.
  • Barry Schwartz, Yakov Ben-Haim, and Cliff Dacso, 2011, What Makes a Good Decision?  Robust Satisficing as a Normative Standard of Rational Behaviour, The Journal for the Theory of Social Behaviour, 41(2): 209-227. Pre-print.
  • Lior Davidovitch and Yakov Ben-Haim, 2011, Is your profiling strategy robust? Law, Probability and Risk. 10: 59-76. pdf preprint.
  • Lior Davidovitch and Yakov Ben-Haim, 2010, Robust Satisficing Voting: Why are uncertain voters biased towards sincerity? Public Choice, vol.145, issue 1, pp.265–280. Pre-print.
  • Yakov Ben-Haim, 2011, When is non-probabilistic robustness a good probabilistic bet? Working paper.
  • Yakov Ben-Haim, 2014, Robust satisficing and the probability of survival, Intl. J. of Systems Science, 45(1): 3-19, appearing on-line 9 May 2012. Online preview.
  • Zacksenhouse, M., R. Bogacz and P. Holmes, 2010, Robust versus optimal strategies for two-alternative forced choice tasks, Journal of Mathematical Psychology, vol. 54, pp.230-246.


    It has been proposed that animals and humans might choose a speed-accuracy tradeoff that maximizes reward rate. For this utility function the simple drift-diffusion model of two-alternative forced-choice tasks predicts a parameter-free optimal performance curve that relates normalized decision times to error rates under varying task conditions. However, behavioral data indicate that only approximately 30% of subjects achieve optimality, and here we investigate the possibility that, in allowing for uncertainties, subjects might exercise robust strategies instead of optimal ones. We consider two strategies in which robustness is achieved by relinquishing performance: maximin and robust-satisficing. The former supposes maximization of guaranteed performance under a presumed level of uncertainty; the latter assumes that subjects require a critical performance level and maximize the level of uncertainty under which it can be guaranteed. These strategies respectively yield performance curves parameterized by a presumed uncertainty level and required performance. Maximin performance curves for uncertainties in response-to-stimulus interval match data for the lower-scoring 70% of subjects well, and are more likely to explain it than robust-satisficing or alternative optimal performance curves that emphasize accuracy. For uncertainties in signal-to-noise ratio, neither maximin nor robust-satisficing performance curves adequately describe the data. We discuss implications for decisions under uncertainties, and suggest further behavioral assays.


    Two-alternative forced-choice; Decision making; Robust decision making; Optimal decision making; Info-gap; Uncertainties; Drift-diffusion models