Dynamic decision making: human control of complex systems.
This paper reviews research on dynamic decision making, i.e., decision making under conditions which require a series of decisions, where the decisions are not independent, where the state of the world changes, both autonomously and as a consequence of the decision maker's actions, and where the decisions have to be made in real time. It is difficult to find useful normative theories for these kinds of decisions, and research thus has to focus on descriptive issues. A general approach, based on control theory, is proposed as a means to organize research in the area. An experimental paradigm for the study of dynamic decision making, that of computer simulated microworlds, is discussed, and two approaches using this paradigm are described: the individual differences approach, typical of German work in the tradition of research on complex problem solving, and the experimental approach. In studies following the former approach, the behaviour of groups differing in performance is compared, either with respect to strategies or with respect to performance on psychological tests. The results show that there are wide interindividual differences in performance, but no stable correlations between performance in microworlds and scores on traditional psychological tests have been found. Experimental research studying the effects of system characteristics, such as complexity and feedback delays, on dynamic decision making has shown that decision performance in dynamic tasks is strongly affected by feedback delays and whether or not the decisions have side effects. Although neither approach has led to any well-developed theory of dynamic decision making so far, the results nevertheless indicate that we are now able to produce highly reliable experimental results in the laboratory, results that agree with those found in field studies of dynamic decision making. This shows that an important first step towards a better understanding of these phenomena has been taken.