Figure 4. The ecological advantage of the stochastic feature.

(a) Illustration that modeled humans’ decision-making behavior at different stages of the mental simulation using the natural gravity simulator (NGS) and mental gravity simulator (MGS). (b) The decision of the linear classifier based on the simulation of the MGS was less accurate than that of the NGS (top), but the decision was made faster in the MGS than in the NGS (middle). The MGS was more efficient than the NGS in combining accuracy and speed (bottom). (c) The relationship between the number of simulations and the variance of the estimated stability. (d) The difference in the variance of the estimated stability between the participants and the MGS. The difference was minimal when the MGS ran the simulation three times. Error bar: standard error.

Figure 4—figure supplement 1. Ecological advantage of the world model embodied with different Gaussian functions.

(a) Prediction accuracy decreased when the variance of the Gaussian function increased, and reached an asymptote of 0.75. (b) Response time decreased as the variance increased and reached an asymptote of 0.20. (c) The prediction accuracy and response time were combined as a measurement for efficiency, which gradually increased monotonically as the function of the variance until an asymptote of 4. Red box: the world model embodied no stochastic characteristic (i.e., the deterministic model); Blue box: the world model with different levels of variances. Error bar: standard error.

Figure 4—figure supplement 2. The relation between the number of simulations and the variance of stability inference.

The simulation showed that the variance of stability inference decreased with the number of simulations. Note that the variance in the world model observed in participants best matched the variance when the simulation of the mental gravity simulator (MGS) was conducted three times.