One line of work has tackled the problem using partially observable Markov decision processes and reinforcement learning with carefully designed action spaces (Young et al., 2013).
the large, hand-designed action and state spaces make this class of models brittle and unscalable, and in practice most deployed dialogue systems remain hand-written, rule-based systems.