The decision theory is defined typically as the combination of utility theory and probability theory. In this paper we generalize the decision theory as the performance measure theory and uncertainty theory. Intelligent agents look for approximate optimal decisions under bounded resources and uncertainty. The $-calculus process algebra for problem solving applies the cost performance measures to converge to optimal solutions with minimal problem solving costs, and allows to incorporate probabilities, fuzzy sets and rough sets to deal with uncertainty and incompleteness.