This paper uses data-driven n-gram user simulations (Georgila et al., 2005a) and a richer dialogue context.
increasing the size of the state space for RL has the danger of making the learning problem intractable, and at the very least means that data is more sparse and state approximation methods may need to be used (Henderson et al., 2005).