Tab. 1.
Comparison of model fits. The table lists the proportion of variance explained (R2) and the Bayesian information criterion (BIC) for the tested models. The models were fitted to the individual data points in Fig. 4 by minimizing the least square error. In addition to the absolute BIC value, the BIC is also provided relative to the BIC for the Random model in which choices are drawn randomly. A lower BIC value indicates a more suitable model. RL: Reinforcement Learning. WSLS: Win-Stay Lose-Shift. The Updated Reinforcement Learning model (Fig. 5) is found to be the most suitable model by the BIC and accounts for most of the variance in the data.
| Random | WSLS | RL | Updated RL | Prospect Utility | Satisficing | Updated Satisficing | |
|---|---|---|---|---|---|---|---|
| R 2 | 0.03 | 0.92 | 0.89 | 0.99 | 0.96 | 0. 88 | 0. 96 |
| BIC | –57.4 | –78.9 | –73.7 | –92.3 | –82.2 | –69.7 | –79.8 |
| BIC (re Random) | 0 | –21.5 | –16.3 | –34.9 | –24.8 | –12.3 | –22.4 |