Tacit Collusion

Tacit collusion, the unspoken coordination of independent entities to achieve anti-competitive outcomes, is increasingly studied in the context of AI-driven systems. Current research focuses on how reinforcement learning algorithms, particularly deep reinforcement learning and Q-learning, enable autonomous agents (like pricing algorithms or AI-controlled market participants) to converge on collusive behaviors without explicit communication, even in complex scenarios like two-sided markets and multi-unit auctions. This research is crucial for understanding and mitigating the potential for AI to undermine fair competition in various sectors, impacting both economic regulation and the design of robust AI systems.