Interactive Agent that Understands the User

Our work uses the notion of theory of mind to enable an interactive agent to keep track of the state of knowledge, goals and intentions of the human user, and to engage in and initiate sophisticated interactive behaviors using decision-theoretic paradigm of maximizing expected utility. Currently, systems like Google Now and Siri mostly react to user’s requests and commands using hand-crafted responses, but they cannot initiate intelligent communication and plan for longer term interactions. The reason is that they lack a clearly defined general objective of the interaction. Our main premise is that communication and interaction are types of action, so planning for communicative and interactive actions should be based on a unified framework of decisiontheoretic planning. To facilitate this, the system’s state of knowledge (a mental model) about the world has to include probabilistic representation of what is known, what is uncertain, and how things change as different events transpire. Further, the state of user’s knowledge and intentions (the theory of the user’s mind) needs to include precise specification of what the system knows, and how uncertain it is, about the user’s mental model, and about her desires and intentions. The theories of mind may be further nested to form interactive beliefs. Finally, decision-theoretic planning proposes that desirability of possible sequences of interactive and communicative actions be assessed as expected utilities of alternative plans.We describe our preliminary implementation using the Open CYC system, called MARTHA, and illustrate it in action using two simple interactive scenarios.