  While interest in conversational recommender systems has been on the rise,
operational systems suitable for serving as research platforms for
comprehensive studies are currently lacking. This paper introduces an enhanced
version of the IAI MovieBot conversational movie recommender system, aiming to
evolve it into a robust and adaptable platform for conducting user-facing
experiments. The key highlights of this enhancement include the addition of
trainable neural components for natural language understanding and dialogue
policy, transparent and explainable modeling of user preferences, along with
improvements in the user interface and research infrastructure.
