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Authors: Reza Refaei Afshar ; Yingqian Zhang ; Murat Firat and Uzay Kaymak

Affiliation: School of Industrial Engineering, Eindhoven University of Technology and The Netherlands

Keyword(s): Online AD Auction, Real Time Bidding, Ad Network, Supply Side Platform, Reinforcement Learning, Predictive Model.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Group Decision Making ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; State Space Search ; Symbolic Systems

Abstract: A high percentage of online advertising is currently performed through real time bidding. Impressions are generated once a user visits the websites containing empty ad slots, which are subsequently sold in an online ad exchange market. Nowadays, one of the most important sources of income for publishers who own websites is through online advertising. From a publisher’s point of view it is critical to send its impressions to most profitable ad networks and to fill its ad slots quickly in order to increase their revenue. In this paper we present a method for helping publishers to decide which ad networks to use for each available impression. Our proposed method uses reinforcement learning with initial state-action values obtained from a prediction model to find the best ordering of ad networks in the waterfall fashion. We show that this method increases the expected revenue of the publisher.

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Paper citation in several formats:
Afshar, R.; Zhang, Y.; Firat, M. and Kaymak, U. (2019). A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy. In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-350-6; ISSN 2184-433X, SciTePress, pages 256-265. DOI: 10.5220/0007395502560265

@conference{icaart19,
author={Reza Refaei Afshar. and Yingqian Zhang. and Murat Firat. and Uzay Kaymak.},
title={A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2019},
pages={256-265},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007395502560265},
isbn={978-989-758-350-6},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - A Reinforcement Learning Method to Select Ad Networks in Waterfall Strategy
SN - 978-989-758-350-6
IS - 2184-433X
AU - Afshar, R.
AU - Zhang, Y.
AU - Firat, M.
AU - Kaymak, U.
PY - 2019
SP - 256
EP - 265
DO - 10.5220/0007395502560265
PB - SciTePress

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