1. A method comprising the steps of: building a forecast for an autonomous agent, said building at least comprising: selecting a policy from a set of policies, said policy mapping states of said autonomous agent to actions of said autonomous agent; and automatically choosing and adding a new forecast to a set of forecasts, said new forecast at least comprising a prediction regarding future states of said autonomous agent during execution and termination of said policy based on a closed-loop sequence of actions, where the policy is considered with conditions for termination of the policy; evaluating a state of said autonomous agent following termination of said policy, said evaluation at least comprising comparing said state with said prediction; creating a new policy that optimizes a function over observable signals and forecasts; building a further new forecast, said further new forecast at least comprising a further prediction regarding future states of said autonomous agent during execution and termination of said new policy based on a closed-loop sequence of actions, where the new policy is considered with conditions for termination of the new policy; evaluating a state of said autonomous agent following termination of said new policy, said evaluation at least comprising comparing said state with said further prediction; and determining whether to build an additional forecast, said determining optionally at least in part based on said evaluation.