Three approaches to the determination of behavioral stability were examined. In the first, a learning curve was fit to acquisition data (from Cumming and Schoenfeld, 1960), and the “experiment” stopped when the data approached sufficiently close to the theoretical asymptote. In the second, the data were analyzed for variability and linear and quadratic trend. In the third, the experiment was stopped when the magnitude of the daily changes in the data fell below a criterion. Accuracy was measured as deviation between the average value of the dependent variable when the experiment was stopped, and the average value over the last 100 sessions. The first approach was most accurate, but at the cost of requiring the most sessions and being the most difficult to apply. Both the second and third approaches provided acceptable criteria with a reasonable cost‐accuracy tradeoff. The second approach permits a continuous adjustment of the criteria to accommodate the variability intrinsic in the experimental paradigm. The third, nomothetic, approach also takes into account the decreasing marginal utility of extended training ses