Learning & Games Reading Group: Learning in the Presence of Strategic Behavior

Title: AI, algorithmic pricing and Collusion
Abstract: Increasingly, algorithms are supplanting human decision-makers in
pricing goods and services. To analyse the possible consequences, we
experimentally study the behavior of independent tabular RL algorithms
interacting with each other and maximising profits in a synthetic
marketplace. We find that the algorithms consistently learn to charge
supra-competitive prices, without communicating with one another. The
high prices are sustained by collusive strategies with a finite phase
of punishment followed by a gradual return to cooperation. In the
second part of the talk, I will summarise a policy debate on
algorithmic pricing bridging together academics in Law, Economics and
Computer Science and introduce a field experiment meant to test the
external validity of our findings.