An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions
Machine Learning
2018-03-07 v1 Machine Learning
Econometrics
Optimization and Control
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.
Cite
@article{arxiv.1803.01968,
title = {An Online Algorithm for Learning Buyer Behavior under Realistic Pricing Restrictions},
author = {Debjyoti Saharoy and Theja Tulabandhula},
journal= {arXiv preprint arXiv:1803.01968},
year = {2018}
}