Proceedings of the 2007 International Conference on Collaborative Technologies and Systems © IEEE, 2007 A New Tactical Group Decision Analysis System (TGDAS) Combining Analytical and Naturalistic Decision Modeling Amos Freedy, Ph.D. Marvin Cohen, Ph.D. Gershon Weltman, Ph.D. Elan Freedy Perceptronics Solutions, Inc. info@percsolutions.com ABSTRACT The Tactical Group Decision Aiding System supports co-located or distributed teams who are planning missions requiring the selection of one among several possible options. Team members propose courses of action by creating scenarios, i.e., causally linked sequences of actions, key factors or events in the past, present, or future, and short or long-term mission outcomes. The TGDAS builds formally correct decision models via a scenario matrix that compares scenarios and identifies significant branch points, and by means of pre-stored editable templates that supply variables and relationships matching the scenario branch points in the relevant type of mission and situation. Model- based analyses order the options and let the collaborative team focus on variables that have the most impact on decisions and outcomes. KEY WORDS: Collaborative Decision Support, Decision Analysis, Naturalistic Decision Making, Auto- mated Facilitation , Tactical Decision Making 1. INTRODUCTION The need for collaborative tactical planning and decision-making is at the center of today’s military and security command and control operations – and of many business operations as well. Associated with this critical need is the problem of aiding and enhancing the capabilities for tactical decision making by distributed collaborative groups. Of particular concern is collaboration across services, agencies and organizations, and in operations involving coalition partners dispersed in different geographical locations. It is clear that computer support systems provide the logical path to aiding and enhancing. But up to now no completely satisfactory computer solution has emerged -- in large part because previous solutions have focused primarily on the decision process and not the product. The field of group decision support systems (GDSS) has been committed to developing interactive computer-based systems which facilitate the solution of unstructured problems by decision makers working together as a team. However, the main objective of GDSS development has been to augment the effectiveness of decision groups through interactive sharing of information among the group members and with the software applications. The focus of these systems is almost entirely on facilitating group interaction, brainstorming and communication. Virtually no attention is paid to underlying decision analytic principles or to support of normative decision making. The problem we have addressed, therefore, is that of developing a computer-based collaborative decision support system that both facilitates interaction and leads to improved decision products. 2. DECISION MODELING The development of Analytical Decision Theory as an overarching framework for Bayesian probability and choice is regarded as among the most significant accomplishments in logic and statistics in the second half of the twentieth century [3][9]. Decision theory provides a rigorous and analytically justified framework for organizing the information and judgments relevant to a decision, specifying relationships among key variables, propagating uncertainty, capturing and weighing objectives, and estimating the overall value and risk of alternative decision options [7][8].