POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS

Moving from limited-domain dialogue systems to open do-main dialogue systems raises a number of challenges. One of them is the ability of the system to utilise small amounts of data from disparate domains to build a dialogue manager policy. Previous work has focused on using data from dif-ferent domains to adapt a generic policy to work for a spe-cific domain. Inspired by Bayesian Committee Machines, this paper proposes the use of a committee of dialogue poli-cies. The results show that such a model is particularly ben-eficial for adaptation in multi-domain dialogue systems and significantly improves performance compared to a single pol-icy baseline. Index Terms — Bayesian committee machines, Gaussian processes, reinforcement learnin