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Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising
[article]
2018
arXiv
pre-print
Real-time advertising allows advertisers to bid for each impression for a visiting user. To optimize specific goals such as maximizing revenue and return on investment (ROI) led by ad placements, advertisers not only need to estimate the relevance between the ads and user's interests, but most importantly require a strategic response with respect to other advertisers bidding in the market. In this paper, we formulate bidding optimization with multi-agent reinforcement learning. To deal with a
arXiv:1802.09756v1
fatcat:f4ikpoio3neyxfziactsvjwdxu