Vector extremal systems in cross-constrained games of regulatory policy analysis and synthesis

Abstract Vector extremal solutions for games with cross-constrained strategy sets are applied to new games for analysis and synthesis of regulatory policy developed herein. They provide constructively, without recourse to point-to-set maps or quasi-variational inequalities, a set of solutions (not just one Nash equilibrium generalization) forecasting normatively players' behavior. A new method of vectorization of player's objectives provides dual problem relations at optimality which for a large class reduces the solution mathematics to ordinary convex programming. This method is developed in the context of a hypothetical example drawn from the privatization of British Telecom.