In task-oriented dialogue systems, as already noted, dialogue modeling is much more challenging, since such systems are expected not only to contribute to solving the domain problem at hand, but to understand the user's utterances, beliefs, and intentions, and to hold their own in a human-like, mixed-initiative dialogue. This requires domain models, general incremental collaborative planning methods, dialogue management that models rational communicative interaction, and thorough language understanding (especially intention recognition) in the chosen domain. Prototype systems have been successfully built for domains such as route planning, air travel planning, driver and pedestrian guidance, control and operation of external devices, emergency evacuation, and medication advising (e.g., Allen et al. 2006; Rich and Sidner 1998; Bühler and Minker 2011; Ferguson and Allen 1998, 2007), and these hold very significant practical promise. However, systems that can deal with a variety of reasonably complex problems, especially ones requiring broad commonsense knowledge about human cognition and behavior, still seem out of reach at this time.