Heuristics and optimal solutions to the breadth-depth dilemma.

ABSTRACT: In multialternative risky choice, we are often faced with the opportunity to allocate our limited information-gathering capacity between several options before receiving feedback. In such cases, we face a natural trade-off between breadth-spreading our capacity across many options-and depth-gaining more information about a smaller number of options. Despite its broad relevance to daily life, including in many naturalistic foraging situations, the optimal strategy in the breadth-depth trade-off has not been delineated. Here, we formalize the breadth-depth dilemma through a finite-sample capacity model. We find that, if capacity is small (∼10 samples), it is optimal to draw one sample per alternative, favoring breadth. However, for larger capacities, a sharp transition is observed, an

SUBMITTER: Moreno-Bote R 

PROVIDER: S-EPMC7443877 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature