Defining an Adaptable Framework for Behaviour Support Agents in Default Logic

In order to provide personalised advice, behaviour support agents need to consider the user’s needs and preferences. This user model should be easily adaptable as the user’s requirements will change during the long-term use of the agent. We propose a formal framework for such an agent in which the knowledge and the beliefs of the agent are represented explicitly and can be updated directly. Our framework is based on ordered default logic as defeasible reasoning allows the agent to infer additional information based on possibly incomplete knowledge about the world and the user. We also define updates on each component of the agent’s framework and demonstrate how these updates can be used to resolve potential misalignments between the agent and the user. Throughout the paper we illustrate our work using a simplified example of a behaviour support agent intended to assist the user in finding a suitable form of exercise.