In this project we are developing a framework that allows a Socially Assistive Robot (SAR) to support the process of habit formation. Habits are formed when cue-behavior pairs are reinforced with rewards over time when a person completes a specified behavior after encountering a cue for that behavior in the environment. We are exploring how a robot can support this process through providing reminders and social rewards for habits that promote health and wellness. This framework addresses the key problem of selecting a support strategy in different circumstances based on information gained from past completion or incompletion of the behavior. We are developing this framework using an iterative process incorporating findings from social psychology and neuroscience into a computational formulation of SAR habit formation support.

This work addresses the following questions in the context of using a SAR to support habit formation.

  1. How should a SAR provide support to a person who is trying to change a behavior?
  2. What set of actions should a SAR choose from in order to support behavior change?
  3. How should a SAR make decisions about what support actions to take?
  4. These research questions will be explored through the development and evaluation of a computational model of habit formation support that allows a robot to take actions to support a person forming a new habit (made up of a specific cue and behavior).