decisions represent the decisions of a solitary soldier or an individual commanding a single vehicle or controlling a lone weapon system; unit-level decisions represent the decisions made by a collection of entities (e.g., group decisions of a staff or the group behavior of a platoon). This chapter addresses only entity-level decisions; unit-level models are discussed in Chapter 10.
Past simulation models have almost always included assumptions about decision processes, and the complexity with which they incorporate these assumptions ranges from simple decision tables (e.g., the recognize-act framework proposed by Kline, 1997) to complex game theoretic analyses (e.g., Myerson, 1991). However, the users of these simulations have cited at least two serious types of problems with the previous models (see, e.g., Defense Advanced Research Projects Agency, 1996:35-39). First, the decision process is too stereotypical, predictable, rigid, and doctrine limited, so it fails to provide a realistic characterization of the variability, flexibility, and adaptability exhibited by a single entity across many episodes. Variability, flexibility, and adaptability are essential for effective decision making in a military environment. Variability in selection of actions is needed to generate unpredictability in the decision maker's behavior, and also to provide opportunities to learn and explore new alternatives within an uncertain and changing environment. Adaptability and flexibility are needed to reallocate resources and reevaluate plans in light of unanticipated events and experience with similar episodes in the past, rather than adhering rigidly to doctrinal protocols. Second, the decision process in previous models is too uniform, homogenous, and invariable, so it fails to incorporate the role of such factors as stress, fatigue, experience, aggressiveness, impulsiveness, and attitudes toward risk, which vary widely across entities. A third serious problem, noted by the panel, is that these military models fail to take into account known limitations, biases, or judgmental errors.
The remainder of this chapter is organized as follows. First is a brief summary of recent progress in utility theory, which is important for understanding the foundation of more complex models of decision making. The second section reviews by example several new decision models that could ameliorate the stereotypic and rigid character of the current models. The models reviewed are sufficiently formalized to provide computational models that can be used to modify existing computer simulation programs, and are at least moderately supported by empirical research. The next section illustrates one way in which individual differences and moderating states can be incorporated into decision models through the alteration of various parameters of the example decision model. The fourth section reviews, again by example, some human biases or judgmental errors whose incorporation could improve the realism of the simulations. The final section presents conclusions and goals in the area of decision making.
As a final orienting comment, it should be noted that the work reviewed here comes from two rather different traditions within decision research. The first,