Description
Empathy is defined as a way of understanding the minds of others and expresses the matching relation between the emotions of two people [1]. Research shows the presence of empathic responses in avatars/robots increases social presence and engagement, trust, positivity, appropriateness, likeability and caring ability, and reduces stresses [2-4]. Generally, the empathic responses are expressed through action tendencies, facial expressions, body expressions, and physiological responses [1]. This project aims to build a computational model for creating empathy on avatars/robots by conducting qualitative analysis through online search engines, such as Web of Science, IEEE, and PubMed.
Goals
Familiarizing with the process to conduct a systematic review.
Exploring machine learning and statistical methods to build a predictive model.
Designing a computational model for measuring robotic empathy.
Requirements
Interesting Reading: Empathy is Key: Ensuring students remain engaged in a hybrid teaching environment, CLT (Centre for Learning and Teaching) Newsletter, ANU, July 2020.
Background Literature
A Paiva, I Leite, H Boukricha, and I Wachsmuth (2017). Empathy in Virtual Agents and Robots: A Survey. Transactions on Interactive Intelligent Systems, 7(3):1-40.
I Leite, G Castellano, A Pereira, C Martinho, and A Paiva (2014). Empathic Robots for Long-term Interaction. International Journal of Social Robotics, 6(3):329-341.
M Ochs, D Sadek, and C Pelachaud (2012). A Formal Model of Emotions for An Emphatic Rational Dialog Agent. Autonomous Agents and Multi-Agent Systems, 24(3):410-440.
B Xiao, ZE Imel, P Georgiou, DC Atkins, and SS Narayanan (2016). Computational Analysis and Simulation of Empathic Behaviors: A Survey of Empathy Modeling with Behavioral Signal Processing Framework. Current Psychiatry Reports, 18(5):1-18.