1. A system for controlling a vehicle using a set of competing adaptable predictive models of the dynamics of the vehicle, the system comprising: one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of: using each competing adaptable predictive model, generating a set of predicted sensory data based on prior sensory data and prior vehicle control inputs, each competing adaptable predictive model comprising a neural network; comparing each set of predicted sensory data with subsequent sensory data collected from the vehicle; using the comparison of each set of predicted sensory data, automatically identifying one of the competing adaptable predictive models as a match; if a match is identified, modifying the adaptable predictive model that is the match according to a second set of sensory data, and controlling the vehicle using control outputs generated using the match; and if a match is not identified, generating a new adaptable predictive model through automatic model learning using the second set of sensory data, and controlling the vehicle using control outputs generated using the new adaptable predictive model.
1. A system for controlling a vehicle using a set of competing adaptable predictive models of the dynamics of the vehicle, the system comprising: one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of: using each competing adaptable predictive model, generating a set of predicted sensory data based on prior sensory data and prior vehicle control inputs, each competing adaptable predictive model comprising a neural network; comparing each set of predicted sensory data with subsequent sensory data collected from the vehicle; using the comparison of each set of predicted sensory data, automatically identifying one of the competing adaptable predictive models as a match; if a match is identified, modifying the adaptable predictive model that is the match according to a second set of sensory data, and controlling the vehicle using control outputs generated using the match; and if a match is not identified, generating a new adaptable predictive model through automatic model learning using the second set of sensory data, and controlling the vehicle using control outputs generated using the new adaptable predictive model. 8. The system as set forth in claim 1 , wherein each competing adaptable predictive model is trained or designed for a distinct vehicle driving scenario.