A method, device and system of prediction of a state of an object in the environment using an action model of a neural network. In accordance with one aspect, a control system for a object comprises a processor, a plurality of sensors coupled to the processor for sensing a current state of the object and an environment in which the object is located, and a first neural network coupled to the processor. One or more predicted subsequent states of the object in the environment are determined using an action model of the neural network and a current state of the object in the environment and an plurality of action sequences. The action model comprises a mapping of states of the object in the environment and actions performed by the object for each state to predicted subsequent states of the object in the environment.