Effort-based decision-making

Choosing between options that differ in benefits and required effort. Varying reward and effort independently helps distinguish reduced reward sensitivity from increased effort cost.^[ref]

Consider a logistic choice rule

P (accept) = 1/ (1 + exp (- U))

with

U = α R - κ E

and fixed noise scale. At one positive offer

(R_{0}, E_{0})

, changes satisfying

δ α R_{0} = δ κ E_{0}

leave utility and acceptance probability unchanged. One offer therefore cannot identify reward gain and effort cost separately.

For example,

(α, κ) = (0.6, 0.2)

and

(1, 1)

both give

U = 1

(R, E) = (2, 1)

. Their predictions differ at other offers. Independently varying reward and effort can identify the two coefficients within this model when the design has rank two and choice data are informative. If noise scale is also unknown, its tradeoff with the coefficients requires additional constraints.

Effort discounting

 0  0

Reduction in the subjective attractiveness of an outcome as required effort increases. The form and strength of the reduction must be estimated under a specified model and task.