Tailoring Evaluative Arguments to User’s Preferences

Abstract

Computer systems that serve as personal assistants, advisors, or sales assistants frequently need to argue evaluations of domain entities. Argumentation theory shows that to argue an evaluation convincingly requires to base the evaluation on the hearer’s values and preferences. In this paper we propose a framework for tailoring an evaluative argument about an entity when user’s preferences are modeled by an additive multiattribute value function. Since we adopt and extend previous work on explaining decision-theoretic advice as well as previous work in computational linguistics on generating natural language arguments, our framework is both formally and linguistically sound.

This work was supported by grant number DAA-1593K0005 from the Advanced Research Projects Agency (ARPA). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of either ARPA or the U.S. Government.