  Unspoken social rules, such as those that govern choosing a proper discussion
topic and when to change discussion topics, guide conversational behaviors. We
propose a computational model of conversation that can follow or break such
rules, with participant agents that respond accordingly. Additionally, we
demonstrate an application of the model: the Experimental Social Tutor (EST), a
first step toward a social skills training tool that generates human-readable
conversation and a conversational guideline at each point in the dialogue.
Finally, we discuss the design and results of a pilot study evaluating the EST.
Results show that our model is capable of producing conversations that follow
social norms.
