How Alibaba Used Reinforcement Learning To Change Real-Time Bidding

Bidding optimisation is considered among toughest critical problems in online advertising. Bidding strategies adopt different search pattern, for example, Sponsored Search (SS) which depends on the randomness of the user's behaviour and the nature of the platform. Display advertising is considered as one of the simple techniques for auction and has taken over Real-Time Bidding resulting in a better performance for the advertisers. In this article, we will explore how Deep Learning techniques are implemented to optimise the Sponsored Search Real Time Bidding (SS-RTB) system in a stochastic environment. A Reinforcement Learning solution for handling the stochastic environment is proposed in the paper titled Deep Reinforcement Learning For Sponsored Search Real Time Bidding by Alibaba group, where the state transition probability is considered for every two days.