Supervision and Control in Engineering and Music"
Dr.-Ing. Leon Urbas
Real time Dynamic Decision Making
in Supervisory Control
The paper outlines some attributes of dynamic human-machine systems
are relevant to classifiy them as real time dynamic decision making
from the persepctive of the human supervisory operator.
Characteristics of Dynamic Human Machine
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:
- Dynamic system: the technical system shows a characteristic
which is not fully changeable due to some limitations of the system.
future development of the technical system without outer influence is
by some memory in form of energy, mass or information storage.
- coupled multiple inputs multiple outputs: Single manipulated
(input) of the system show influence on more than one observable state
variable of the system. This can be the cause for conflicting goals.
instance, raising the throughput in processes of the chemical
often shows a contra productive effect in product quality.
- latent variables: The knowledge of manifest (direct observable)
is not sufficient to interpret current or anticipate future behaviour
the system. Instead it is necessary to deduce latent variables from
of manifest and manipulated variables.
- time variant dynamics: endogenous disturbances or deliberate
topology of the system may have great influence on the dynamic
of the system due to new or fading interactions between different parts.
- open: the technical system is affected by exogenous disturbances
most often are not direct observable - it is necessary to deduce them
unusual behaviour of the system.
- real time: activities or sequels of activities have to be
certain deadlines to reach the intended goal. There are no means to
freeze or rewind the technical system.
The characteristics mentioned above, especially the ad hoc unknown
latent variables and the exogenous disturbances make the
problem ill-defined: start and end of the problem are unknown and may
during the problem solving process. Due to the real time
the time available is limited. Latent state variables and internal
of variables complicates the acquisition of accurate knowledge about
system. In consequence only limited time and uncertain knowledge is
to the responsible operator to judge about new situations, make a
and put goal oriented activities into execution. The mental models in
task environments, that can be deduced from learning through
and observation are generally only partial homomorphous, i.e. we
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
of a single variable are fundamentally different from the requirements
for a structural qualitative mental model which helps in failure
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
resources. We assume that generally strategies with low execution time
and low demand for cognitive resources are chosen, as long as the
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
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
of the interface.
- a priori strategy: The current state is anticipated by the mental
and recent observations, and may be followed by an activity where some
critical variables are compared.
- a posterior strategy: The current state is reconstructed from
of current data over some period and may be some historical data. This
passive strategy may be coupled with well-directed manipulation of some
- erratic strategy: interact by random and hope for the best.
Operator Modeling and Music
If we want to compare the conductor and his orchestra with the
operator and his technical system from the perspective of common
models, the author believes, that it is necessary to have a close look
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
this task. Some questions, which arise from current considerations,
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
when the score assigns their instrument to pause?