1. A computer-implemented method for learning a policy for performing a task by a computing system, the method comprising the steps of: determining a first state associated with a first time interval; determining a subsequent state associated with a subsequent time interval; determining a first action from the first state using the policy, which comprises a plurality of weights, properties of one or more actions and properties of one or more states; determining a subsequent action from the subsequent state using the policy; determining a reward value associated with a combination of the first state and the first action; and storing a state description including the first state, the first action, the subsequent state, the subsequent action and the reward value.