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Two pricing problems are solved by using asymmetric multiagent reinforcement learning methods in this paper. In the first problem, a flat pricing scenario, there are two competing brokers that sell identical products to customers and compete on the basis of price. The second problem is a hierarchical pricing scenario, where a supplier sells products to two competing brokers. In both cases, the methods converged and led to very promising results. We present a brief literature survey of pricing models based on reinforcement learning, introduce the basic concepts of Markov games and solve two pricing problems based on multiagent reinforcement learning.
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on (Volume:2 )
Date of Conference: 25-29 July 2004