Artificial intelligence

Reinforcement learning algorithms have been shown able to collude on supracompetitive prices when playing pricing games. However, the literature suggests that collusion may not be robust to alternative setups of the game. We simulate models where the algorithms are constrained in production capacity. Our findings suggest that capacity constraints may lead to cycling behavior and high prices as a consequence. We do not find evidence that the cycling behavior is due to tacit collusion.
This paper won the “Prize for the best PhD paper 2024” at the 46th Annual Meeting of the Norwgeian Association of Economists.