Zollman Bandit Model

A bandit model by Kevin Zollman, which depicts how highly connected scientific networks can come to consensus quicker - but may be less accurate than more sparsely connected community. View the full paper here.

Abstract

Increasingly, epistemologists are becoming interested in social struc- tures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a com- munity of scientists is, as a whole, more reliable when its members are less aware of their colleagues’ experimental results. Second, there is a robust trade-off between the reliability of a community and the speed with which it reaches a correct conclusion.

Model Details

Parameters include

• Size of network
• Objective probability of B
• Objective probability of A
• Network structure: complete, cycle, wheel