We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
We present an integrated approach for reasoning about and learning conversation patterns in multiagent communication. The approach is based on the assumption that information abou...
Michael Rovatsos, Felix A. Fischer, Gerhard Wei&sz...
We consider the problem of browsing the top ranked portion of the documents returned by an information retrieval system. We describe an interactive relevance feedback agent that a...