Pragmatic question answering: A game-theoretic approach

We present results of quantitative evaluations of a content selection scheme for answer generation in sales dialogue which is based on an interactive game-theoretic model of the dialogue scenario. The model involves representing a probability distribution over possible customer requirements, i.e., needs that must be met before a customer will agree to buy an object. Through game-theoretic analysis we derive a content selection procedure which constitutes an optimal strategy in the dialogue game. This procedure is capable of producing pragmatically appropriate indirect answers to yes/no questions, and is implemented in an online question answering system. Evaluation results show that these answers are pragmatically natural and contribute to dialogue efficiency. The model allows for systems that learn probabilities of customer requirements, both online and from previous data.