A semantic architecture for artificial conversations

Artificial conversations have many applications in chatter bot-based customer service including website navigation tools and guided online shopping. Existing approaches to generating conversations leverage linguistic and stochastic principles, where lower level grammatical and structural artifacts are modeled. These approaches perform well in pairwise utterance exchanges, but not so well in longer conversational contexts. We simulate more meaningful chatter bot conversations using an architecture that can leverage content and context. Grice's cooperative maxims, which form the central idea in the theory of pragmatics, is our framework for evaluation. The domain of our research is customer service situations, and we compare our artificial conversations with actual conversations of existing chatter bots deployed in the same domain.