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In a future of widespread algorithmic pricing, inadvertent cooperation between algorithms is easier than ever, resulting in coordinated price rises. While governments have clear cut laws to assess and deter traditional collusion, automated pricing poses interesting questions as to what will or will not be allowed. We build and demonstrate how a Q-learner algorithm, even under extremely innocent conditions, can reach a collusive outcome in a virtual marketplace.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
