Modeling Recommendation Systems as Reinforcement Learning Problem

In this era, a massive volume of information is available to the users through web which leads to information overload. The Recommender systems are used to facilitate the search through this vast space of items by giving user personalised services and items. The vast majority of traditional recommendation systems consider the recommendation procedure as a static process and make recom- mendations following a fixed strategy. A user interacts with recommendation engine in a sequence of exchanges of recommendations and provides feedback on them. Hence, we should also try to incorporate the feedback ofthe user at each time step while recommending items at the next time step.