Entropy-Based Techniques for Improved Automated Selection in Computer-Based Reasoning Systems

Techniques for improved automated selection in computer-based reasoning systems are presented. The techniques include receiving context data for operation of a system, determining two or more candidate actions to take, each from a different computer-based reasoning model, and determining the surprisal of each. The surprisals are then compared and, in some embodiments, the one with the lowest surprisal is chosen. In some embodiments, this chosen action is performed on the system. In some embodiments, the chosen action is passed up a control hierarchy for consideration along with entropy and other factors, and the action chosen at that level is performed on the controlled system.