model works, assuming several schemes of decision aggregation. Section \[s:comparison\] compares the introduced models and provides insight into further experimental and theoretical work. Section \[s:conclusion\] concludes the paper.

Model of discrimination {#s:discrimination}
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Consider an experiment in which a participant has to make simple discriminatory decisions of varying difficulty. Each trial is assigned a parameter, $c$, that describes the physical distance between stimuli (e.g., in the Bahrami et al. experiment $c$ was the difference in contrast between Gabor patches). Negative $c$ describes a situation in which the right choice is the first of the pair, whereas positive $c$ describes the opposite situation. The absolute value of $c$ reflects the difficulty of a given trial. The lower the value, the more difficult is the resulting trial. From now on, we refer to the parameter describing physical difference as [*stimulus c*]{}. In the case of Bahrami et al. experimental setup, it can be interpreted as the two-interval stimulus with the difference of contrasts equal to $c$.

By knowing the choices of a certain decision-making agent (in our case either a single participant or a group making the decision together) for a range of stimuli, we can construct a mathematical description of the 