1. A computer-implemented method for pervasive model adaptation, comprising: providing a production plan to a production system, the production plan including a sequence of actions; executing the production plan in the production system; collecting observation data produced by at least one sensor in the production system during execution of the production plan into a computer memory; calculating changes to be made to a system model in the computer memory based on the collected observation data; dynamically updating the system model according to the calculated changes; creating an updated production plan based at least partially on the dynamically updated system model; and storing the updated production plan within the computer memory; wherein the system model is a representation of what is believed to be true about the production system; wherein the production plan and dynamically updated production plan are optimized to provide optimal productivity while concurrently or substantially simultaneously optimized to provide maximum information content value for dynamically updating the system model; wherein the creating an updated production plan based at least partially on the dynamically updated system model comprises: creating a directed graph based on internal constraints of the production system; performing a best-first search algorithm on the directed graph by utilizing an information content function as the evaluation function for the best-first search algorithm to produce a path that maximizes information content; and setting the path produced by the best-first search algorithm as the updated production plan; and, wherein the information content function utilizes a Kalman filter.