Impression Allocation and Policy Search in Display Advertising

no code implementations • 11 Mar 2022 • Di wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee

In order to address the unstable traffic pattern challenge and achieve the optimal overall outcome, we propose a multi-agent reinforcement learning method to adjust the bids from each guaranteed contract, which is simple, converging efficiently and scalable.

Multi-agent Reinforcement Learning

A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising

no code implementations • 10 Sep 2018 • Di Wu, Cheng Chen, Xun Yang, Xiujun Chen, Qing Tan, Jian Xu, Kun Gai

With this formulation, we derive the optimal impression allocation strategy by solving the optimal bidding functions for contracts.

Multi-agent Reinforcement Learning reinforcement-learning +1

Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising

no code implementations • 23 Feb 2018 • Di Wu, Xiujun Chen, Xun Yang, Hao Wang, Qing Tan, Xiaoxun Zhang, Jian Xu, Kun Gai

Our analysis shows that the immediate reward from environment is misleading under a critical resource constraint.

Marketing reinforcement-learning +1