Generating Discourse across Several User Models: Maximizing Belief while Avoiding Boredom and Overload

In this paper we present a content planning system which takes into consideration a user's boredom and cognitive overload Our system applies a constraint-based optimization mechanism which maximizes a probabilistic function of a user's beliefs, and uses a representation of boredom and overload as constraints that affect the possible values of this function Further, we discuss two orthogonal policies for relaxing the parameters of the communication process when these constraints are violated conveying less information or breaking up the material into smaller chunks