Algorithmic Cooperation

Algorithmic Cooperation

Bernhard Kasberger

Heinrich Heine University Dusseldorf - Duesseldorf Institute for Competition Economics (DICE)

Simon Martin

Heinrich Heine University Dusseldorf - Duesseldorf Institute for Competition Economics (DICE)

Hans-Theo Normann

Heinrich Heine University Dusseldorf - Department of Economics; Max Planck Institute for Research on Collective Goods

Tobias Werner

Center for Humans and Machines / Max Planck Institute for Human Development; Heinrich Heine University Dusseldorf - Duesseldorf Institute for Competition Economics (DICE)

Abstract

Algorithms play an increasingly important role in economic situations. These situations are often strategic, where the artificial intelligence may or may not be cooperative. We study the deter-minants and forms of algorithmic cooperation in the infinitely repeated prisoner’s dilemma. We run a sequence of computational experiments, accompanied by additional repeated prisoner’s dilemma games played by humans in the lab. We find that the same factors that increase human cooperation largely also determine the cooperation rates of algorithms. However, algorithms tend to play different strategies than humans. Algorithms cooperate less than humans when cooperation is very risky or not incentive-compatible.