Computable and computational complexity theoretic bases for Herbert Simon's cognitive behavioral economics

This paper aims to interpret and formalize Herbert Simon's cognitive notions of bounded rationality, satisficing and heuristics in terms of computability theory and computational complexity theory. Simon's theory of human problem solving is analyzed in the light of Turing's work on Solvable and Unsolvable Problems. It is suggested here that bounded rationality results from the fact that the deliberations required for searching computationally complex spaces exceed the actual complexity that human beings can handle. The immediate consequence is that satisficing becomes the general criterion of decision makers and heuristics are the procedures used for achieving their goals. In such decision problems, it is demonstrated that bounded rationality and satisficing are more general than orthodox, non-cognitive, Olympian rationality and optimization, respectively, and not the other way about.