As a result, operators need decision support which encodes operational experience to allow them to control systems with less detailed system knowledge. Such a system could serve as such an institutional memory. To be effective, such a system must ensure that operators can understand, supervise, intervene in real-time, and maintain the knowledge base of the system. Additionally, should the automated control system reach a state from which it cannot perform further automatic control activities, it must support the operator's situation assessment and remediation activities. The following sections describe the background and a proposed conceptual architecture for this approach.
Problems can be ill-structured either with respect to problem identification or remediation.
In the case of many complex dynamic systems, operators may have trouble in identifying the exact nature of the problem. Once a problem has been identified, the correct solution procedure may not be apparent, or even known by that operator. To guide problem identification, experienced operators often generate expectancies based on the nature of the problem and previous experience, which they then try to confirm. Based on a situation assessment and previous experience, experts formulate solutions for the current situation and evaluate them using mental simulation in order to determine their applicability to the current problem. Once a satisfactory solution is found it is applied to the problem.