Method for creating predictive knowledge structures from experience in an artificial agent

摘要

Building a forecast for an autonomous agent at least comprises assigning a selected parameter of the autonomous agent to a scalar variable, adding a new policy to a set of policies where the new policy maps internal states of the autonomous agent to actions of the autonomous agent in which the mapping may optimize the scalar variable, and adding a new forecast to a set of forecasts where the forecast at least comprises a prediction regarding future values of the scalar variable following execution of the new policy, regardless whether the agent ever actually chooses to take actions in accordance with said new policy. A state of the autonomous agent may be evaluated following completion of each of the agent's actions by comparing the agent's state information with the predicted values of one or more forecasts. Whether to build an additional forecast may be determined based on the evaluation.