Engineering and Music
"Human Supervision and Control in Engineering and Music"



Workshop
Orchestra Concert
Ensemble Concert
About us

Dr.-Ing. Leon Urbas

Real time Dynamic Decision Making 

in Supervisory Control
 
Abstract
The paper outlines some attributes of dynamic human-machine systems which are relevant to classifiy them as real time dynamic decision making systems from the persepctive of the human supervisory operator. 
 
Characteristics of Dynamic Human Machine Systems
Our research has its focus on modelling of cognitive behaviour of human operators in dynamic human-machine-systems. The class of systems we are looking at can be characterised by the following attributes:
 


The characteristics mentioned above, especially the ad hoc unknown latent variables and the exogenous disturbances make the decision-making problem ill-defined: start and end of the problem are unknown and may change during the problem solving process. Due to the real time characteristics the time available is limited. Latent state variables and internal coupling of variables complicates the acquisition of accurate knowledge about the system. In consequence only limited time and uncertain knowledge is available to the responsible operator to judge about new situations, make a decision, and put goal oriented activities into execution. The mental models in such task environments, that can be deduced from learning through interaction and observation are generally only partial homomorphous, i.e. we assume 
that the relevant structure of the system can be mapped only partially on the mental model. This makes sense from an economic perspective: the requirements for a functional mental model which is useful for the control of a single variable are fundamentally different from the requirements for a structural qualitative mental model which helps in failure diagnosis.
 

Decision Making under Pressure of Time
Rational behaviour in real time dynamic decision-making systems in the sense of good adaptation to the task environment makes it necessary to revert to strategies, which reduce the need for time and cognitive processing resources. We assume that generally strategies with low execution time and low demand for cognitive resources are chosen, as long as the subjective necessary power of anticipation can be reached. How effort and power of anticipation may be 
represented or calculated in a cognitive architecture is not clear at the moment and object of research. To clarify things, some examples for generic strategies are sketched which differ in their need of time and the demand for cognitive resources: It depends on the task environment, whether a strategy is successful and in this sense adequate. The strategy of choice may be influenced by the structure of the domain, the task itself, the necessary level of detail and the engineering design of the supervisory control systems, i.e. the task sharing between automation and human operator as well as the design of the interface. 
 
Operator Modeling and Music
If we want to compare the conductor and his orchestra with the supervisory operator and his technical system from the perspective of common cognitive models, the author believes, that it is necessary to have a close look on the 
characteristics of the dynamic task environment, the tasks, the problem solving strategies and the actions which can be compared or have to be distinguished. The workshop is a highly welcome opportunity to start with this task. Some questions, which arise from current considerations, are: Is every orchestra able to play any score? If not, what are the limits? Is conducting a real time decision making task? What are musicians doing, when the score assigns their instrument to pause?