System personalization is a smart way to handle interaction with various types of customers that come with different preferences. In this project we attempt to optimize the sequential decision processes during the interaction between an online hotel reservation service and its customer. We use POMDP framework to determine the best response for the system. POMDP is suitable for this problem because it takes into account the non-observability of the customer preferences, and the uncertainty of the observations that come from the customer. We present our findings regarding the potential improvement by utilizing belief information, and the sufficient level of observation certainty in order to keep the model considerably useful. We also show the resulting policies trees with the belief information in order to clarify the intuition behind the actions planne
