Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology

29 May 2019Eugene IeVihan JainJing WangSanmit NarvekarRitesh AgarwalRui WuHeng-Tze ChengMorgane LustmanVince GattoPaul CovingtonJim McFaddenTushar ChandraCraig Boutilier

Most practical recommender systems focus on estimating immediate user engagement without considering the long-term effects of recommendations on user behavior. Reinforcement learning (RL) methods offer the potential to optimize recommendations for long-term user engagement... (read more)

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