Adaptive Data-Driven Persuasive Communication for a Conversational Agent to Support Behavior Change

Adaptive Data-Driven Persuasive Communication for a Conversational Agent to Support Behavior Change

Albers, N. (TU Delft Interactive Intelligence)
Brinkman, W.P. (TU Delft Interactive Intelligence)
Neerincx, M.A. (TU Delft Interactive Intelligence)

2021

A human therapist continuously adapts how they persuade a client to adhere to a behavior change intervention based on theoretical expertise, past experience with the client as well as other clients, and the client's current situation. We aim at incorporating these elements into the persuasive communication of a conversational agent that acts as a virtual coach for smoking cessation and physical activity increase. The focus thereby is on investigating how three coaching elements, goal-setting, data-monitoring and the assignment of activities, can be designed to enhance treatment adherence. A first experiment is currently finished to 1) get user input for the interaction design based on interaction scenarios, 2) gather data for and test a reinforcement learning-approach to persuading people to do small preparatory activities for smoking cessation and increasing physical activity, and 3) gain insights into the acceptance and perceived motivational impact of the virtual coach used to persuade people.

Conversational agent
Virtual coach
Persuasion
Reinforcement learning
Personalization
Behavior change
Smoking cessation

http://resolver.tudelft.nl/uuid:c5f11da8-6d13-4f8c-8468-816e1d8b5429

Doctoral Consortium of the ACM International Conference on Intelligent Virtual Agents (IVA '21), 2021-09-14 → 2021-09-17

Institutional Repository

abstract

© 2021 N. Albers, W.P. Brinkman, M.A. Neerincx