Georgia Institute of Technology
Title: Bounding Rationality With Computation
Traditional microeconomic theory treats individuals and institutions as completely understanding the consequences of their decisions given the information they have available. These assumptions might require these agents to solve hard computational problems to optimize our choices. What happens if we restrict the computational power of economic agents?
There has been some work in economics treating computation as a fixed cost or simply considering the size of a program. This series of talks, based on the work of the speaker and others, will explore a new direction bringing the rich tools of computability and computational complexity into economic models.
We show how to incorporate computability and computational complexity into a number of economic models including game theory, prediction markets, forecast testing, preference revelation and awareness. We will suggest a number of further directions worth exploring.
We will not assume any background in economics or computational complexity.