Optimal Allocation of Finite Sampling Capacity in Accumulator Models of Multialternative Decision Making.

ABSTRACT: When facing many options, we narrow down our focus to very few of them. Although behaviors like this can be a sign of heuristics, they can actually be optimal under limited cognitive resources. Here, we study the problem of how to optimally allocate limited sampling time to multiple options, modeled as accumulators of noisy evidence, to determine the most profitable one. We show that the effective sampling capacity of an agent increases with both available time and the discriminability of the options, and optimal policies undergo a sharp transition as a function of it. For small capacity, it is best to allocate time evenly to exactly five options and to ignore all the others, regardless of the prior distribution of rewards. For large capacities, the optimal number of sampled accumulators g

SUBMITTER: Ramirez-Ruiz J 

PROVIDER: S-EPMC9285422 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature