Using Non-Monotonic Logics to Create a Dynamic Framework for a Behavior Support Agent

Abstract

Behavior support agents can assist humans in accomplishing a variety of goals by suggesting actions that promote the desired outcome while being in line with the user’s needs and preferences. In order to make these agents more effective, flexible and responsible, this research aims to create a framework which allows for more interaction between the agent and the user. By using techniques from non-monotonic reasoning, this work aims to model the knowledge base of the agent so that it aligns with the user’s mental model and is able to be modified by the user through new input. In order for the agent to be able to explain its output to the user, the reasoning process needs to be explicit and traceable, which this work intends to incorporate into a logical framework.