Indian Buffet Game with non-Bayesian social learning
How users in a dynamic system perform learning and make decision become more and more important in numerous research fields. In this paper, we propose an Indian Buffet Game to study how users in a dynamic system learn the uncertain system state and make multiple concurrent decisions by not only considering the current utility, but also taking into account the influence of subsequent users' decisions. We analyze the proposed Indian Buffet Game under two different scenarios: one is customers has budget constraint and the other is without budget constraint. For both cases, we design recursive best response algorithms to find the subgame perfect Nash equilibrium for customers. Moreover, we introduce a non-Bayesian social learning algorithm for customers to learn the system state. Finally, we conduct simulations to validate the effectiveness and efficiency of the proposed algorithms.