Minimizing information acquisition costs

Abstract Today, many organizations are investing heavily in expert systems. Unfortunately, many of these systems will fail to deliver the maximum possible value to their investors because little attention has been paid to the cost of providing these systems with the information they require to make a decision. In an expert system, the cost of providing the information that the system requires can be substantial. Minimizing information costs without affecting the decisions made by the system can reduce the cost of operating the system and thereby increase value. We develop an algorithm that determines an optimal information acquisition strategy for an existing system and show how a specific information acquisition strategy can be implemented. Because of the computational complexity of the algorithm, we also develop a simpler, heuristic solution to the problem. Our tests indicate that the heuristic performs very well. Prolog implementations for the same problem, on the other hand, perform poorly.