An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions

Debjyoti Saharoy and Theja Tulabandhula

Papers from arXiv.org

Abstract: We propose a new efficient online algorithm to learn the parameters governing the purchasing behavior of a utility maximizing buyer, who responds to prices, in a repeated interaction setting. The key feature of our algorithm is that it can learn even non-linear buyer utility while working with arbitrary price constraints that the seller may impose. This overcomes a major shortcoming of previous approaches, which use unrealistic prices to learn these parameters making them unsuitable in practice.

Date: 2018-03
New Economics Papers: this item is included in nep-com and nep-upt
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