Zhongcui Ma

The Adaptive Q-Network for Recommendation Tasks with Dynamic Item Space

Reinforcement learning (RL) algorithms can improve recommendation performance by capturing long-term user-system interaction. However, current RL-based recommendation tasks seldom consider the dynamism of the environment, and standard RL algorithms are ineffective in recommending items dynamically.…