approaches that would rectify these problems. In the top-down modeling tradition, a key problem with previous decision models is that 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. We have presented a series of models in increasing order of complexity that are designed to overcome these problems. The first stages in this sequence are the easiest and quickest to implement in current simulation models; the later stages will require more effort and are a longer-term objective. Second, the decision process as currently represented is too uniform, homogenous, and invariable, so it fails to display individual differences due to stress, fatigue, experience, aggressiveness, impulsiveness, or risk attitudes that vary widely across entities. We have outlined how various individual difference factors or state factors can be incorporated by being related to parameters of the existing decision models.
We have also identified research opportunities and a research strategy for incorporating work in the bottom-up, phenomenon-focused tradition into models of military decision making. The thrust proposed here is not toward general understanding and representation of the phenomena, but toward specific empirical research in military settings, using military tasks, personnel, and practices. Problem identification studies would identify specific decision topics that modelers see as important to the simulations and behavioral researchers see as potentially problematic, but amenable to fruitful study. Focused empirical research would assess the extent and significance of these phenomena in specific military contexts. And simulation-compatible representations would be developed with full sensitivity to specific effect-size estimates and contextual moderators. Model realism would improve incrementally as each of these phenomenon-focused submodels was implemented and tested. Progress along these lines holds reasonably high promise for improving the realism of the decision models used in military simulations.
Include judgmental errors such as base-rate neglect and overconfidence as moderators of probability estimates in current simulation models.
Incorporate individual differences into models by adding variability in model parameters. For example, variations in the tendency to be an impulsive versus a compulsive decision maker could be represented by variation in the threshold bound required to make a decision in sequential sampling decision models.
Inject choice variability in a principled way by employing random-utility models that properly represent the effect of similarity in the consequences of each action on choice.
Represent time pressure effects and relations between speed and accuracy of decisions by employing sequential sampling models of decision making.