A Formal Model of Creative Decision Making

Abstract

Real-world tasks are often complex, uncertain, and constrained. The complexity arises from the need to consider numerous factors that are of varying degrees of relevance to the problem at hand. The uncertainty springs from imperfect information concerning the state of the world, the repertoire of feasible alternatives, and the consequences of each action. The constraints are attributable to time, money, and computational resources as well as individual tastes and societal values. Despite the rich nature of practical tasks, previous work in decision making-whether in engineering, statistics, management, or economics-has focused solely on partial aspects of the problem. This state of affairs is reflected in the nomenclature, which involves categories such as "constrained optimization" or "decisions under uncertainty". If real-world tasks are to be addressed in a coherent fashion, it is imperative to develop a systematic framework providing an integrated view. The framework may then serve as the foundation for a general theory of decision making that can capture the full richness of realistic problems. This paper explores how these goals might be achieved. Algebraic and stochastic models of innovative decision making are presented. This is followed by an examination of idea generation in product design. Finally, suggestions are made for extending the work along both theoretical and empirical lines.