Simulated policies for the AC-HAFVF as a function of reward variance <i>β</i>_<i>j</i> and number of effective observations <i>κ</i>_<i>j</i>, for a fixed value of posterior mean rewards (<i>μ</i>₁ = −<i>μ</i>₂ = 1), shape parameter <i>α</i>₁ = <i>α</i>₂ = 3 threshold <i>ζ</i> = 2, start point <i>z</i>₀ = <i>ζ</i>/2 and <i>τ</i> = 0.

A. Choices were more random for more noisy reward distributions (i.e. high values of βj) and for mean estimates with a higher variance (i.e. with a lower number of observations κj). B. Decisions were faster when the difference of the means was clearer (high κj) and when the reward distributions was noisy (high β). Subjects were slower to decide what to do for noisy mean values but precise rewards, reflecting the high cognitive cost of the decision process in these situations.