The last frame from each MLP-MD trajectory is evaluated by a chosen selector to determine whether the structure will be added to the training set or not. If the frame is not selected, the index n is increased, and the MD simulation continues to ensure gradual and continuous exploration of the PES. The automated process iterates until the MD simulation reaches the maximum time (1 ps by default) or the maximum number of AL iterations with a default value of 50. The resulting MLP is then considered final, and its performance is validated on testing data sets generated independently. Exploration of the PES can be performed by MLP-MD using downhill dynamics, WT-MetaD, or WTMetaD-IB during the AL (Fig. ). In the first case, training starts from a predefined TS, represented by the stationary dark blue points in the left panel of Fig. . Random displacements around this point provide the initial configurations for the first version of the MLP. Each iteration involves propagating downhill MLP-MD simulations towards either the RS or PS, with the direction determined by the randomly assigned initial velocities.