Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Asymptotic Optimality of Myopic Optimization in Trial-Offer Markets with Social Influence / 2458
Andrés Abeliuk, Gerardo Berbeglia, Felipe Maldonado, Pascal Van Hentenryck

We study dynamic trial-offer markets, in which participants first try a product and later decide whether to purchase it or not. In these markets, social influence and position biases have a greater effect on the decisions taken in the sampling stage than those in the buying stage. We consider a myopic policy that maximizes the market efficiency for each incoming participant, taking into account the inherent quality of products, position biases, and social influence. We prove that this myopic policy is optimal and predictable asymptotically.