Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We investigate, in an experimental setting, the behavior of single decision makers who at discrete time intervals over an "infinite" horizon may choose one action from a set of possible actions where this set is constant over time, i.e. a bandit problem. Two bandit environments are examined, one in which the predicted behavior should always be myopic (the two-armed bandit) and the other in which the predicted behavior should never be myopic (the one-armed bandit). We also investigate the comparative static predictions as the underlying parameters of the bandit environments are changed. The aggregate results show that the behavior in the two bandit environments are quantitatively different and in the direction of the theoretical predictions.