This paper explores the distinction between normative and positive theoretical statements in a game theoretic context from a Bayesian perspective. Normative and positive theoretical statements are often confused in decision making research. The confusion results from some unique epistemological and methodological problems associated with cognitive behavior as an object for scientific inquiry. The confusion persists because of poor model validation procedures which are themselves further complicated by the confusion. The confusion greatly impedes the development of more useful prescriptions for and predictions of human decision behavior. From a Bayesian perspective which acknowledges the importance of incomplete information and imperfect theories of behavior, the confusion is unnecessary.

Reply to Harsanyi, J. C. 1982. Comment—Subjective probability and the theory of games: comments on Kadane and Larkey's paper. Management Sci. 28 (2) 120–124.

This paper explores some of the consequences of adopting a modern subjective view of probability for game theory. The consequences are substantial. The subjective view of probability clarifies the important distinction between normative and positive theorizing about behavior in games, a distinction that is often lost in the search for “solution concepts” which largely characterizes game theory since the work of von Neumann and Morgenstern. Many of the distinctions that appear important in conventional game theory (two-person versus n-person, zero-sum versus variable sum) appear unimportant in the subjective formulation. Other distinctions, such as single play versus repetitive-play games, appear to be more important in the subjective formulation than in the conventional formulation.

Differences in players' skill are important determinants of relative player success in most real games such as poker, chess, basketball, business, and politics. Yet conventional game theory has concentrated primarily on games with no skill differences among players. This paper uses a simplified version of stud poker to better understand the concept of differential player skill in games. Players with very different strategies for playing this game are modeled algorithmically and pitted against one another in simulation tournaments.