Personalized pricing, which involves tailoring prices based on individual characteristics, is
commonly used by firms to implement a consumer-specific pricing policy. In this process …

With unprecedented access to consumer information, firms are increasingly interested in
designing highly effective data-driven targeting policies based on detailed consumer data …

Reinforcement Learning (RL) is a widely researched area in artificial intelligence that
focuses on teaching agents decision-making through interactions with their environment. A …

We consider how to make dynamic pricing decision for Chinese Online (COL) at T time-
points, an online publisher that allow authors to sell their ongoing book projects. Instead of …

Problem definition: Assortment selection and marketing mix allocation are critical decisions
for retail ers, directly influencing consumer choices. In this paper, we propose a multinomial …

We consider the stochastic contextual bandit problem in the PAC setting. Fix a distribution ν
over a potentially countable 1 set of contexts C. The action space is A, and for computational …