In this project, the Principal Investigator will develop decision analytic methods for multiple decision makers that prescribe one decision maker's decisions while descriptively modeling the decisions of the other decision makers. Decision analysis and game theory have been used extensively to assist in making counter-terrorism decisions. Recently, methods have been proposed to allow treatment of defender decisions, attacker decisions, and uncertainties in one decision model. However, these combined approaches assume that both the attacker and defender are rational decision makers. The rationality assumption is appropriate for the defender as the decision analyst is working in a prescriptive mode to help the defender make a rational and optimal decision. Descriptive decision theory focuses on how real people actually think and behave. Such models are judged by their validity in predicting the actual choices people make and capture many of the ways in which people deviate from the rational, prescriptive ideal. These theories are more appropriate for modeling the attacker's decision. This research will require the development of algorithms that can solve complex influence diagrams with multiple decision makers using prescriptive theories for the defender and descriptive theories for the attacker. We will also develop descriptive decision models for multi-attribute decisions and incorporate them in the prescriptive/descriptive approach.
In terms of broader impacts, this research will benefit the field of homeland security by incorporating more realistic models of attacker behavior while still providing the optimal, rational prescribed action of the defender. It will also benefit general decision theory. The approach is applicable to all decision situations where there are multiple decision makers and an analyst is attempting to prescriptively help one of them make better decisions under uncertainty while modeling the decisions made by the other decision makers. Such situations occur in competitive bargaining and negotiation, marketing and strategy, as well as other general business decisions. Furthermore, while the focus of this research is to prescriptively help one side make better decisions faced with a descriptive model of the other side, there is the potential for this approach to be used in a descriptive science such as economics or political science, where the researcher believes one player in a game is best modeled as rational while the other is best modeled as boundedly rational. The results of this research will be disseminated to both prescriptive and descriptive decision researchers to show that the true power of these methods is found when they are brought together. We will develop iPad software to construct and analyze such models graphically through an intuitive touch interface. This could significantly increase the number of people exposed to this research and the methodologies it integrates.
