To do this effectively, AI agents need to go beyond planning with their own models of the world, and take into account the mental model of the human in the loop. At a minimum, AI agents need approximations of the human's task and goal models, as well as the human's model of the AI agent's task and goal models.
Sarath Sreedharan is a Ph.D. student at Arizona State University working with Prof. Subbarao Kambhampati. His primary research interests lie in the area of human-aware and explainable AI, with a focus on sequential decision-making problems. Sarath’s research has been featured in various premier research conferences, including IJCAI, AAAI, AAMAS,ICAPS, ICRA, IROS, etc., and journals like AIJ. He was also the recipient of Outstanding Program Committee Member Award at AAAI-2020.Anagha Kulkarni is an AI Research Scientist at Invitae. Before that, she received her Ph.D. in Computer Science from Arizona State University. Her Ph.D. thesis was in the area of human-aware AI and automated planning. Anagha’s research has been featured in various premier conferences like AAAI,IJCAI, ICAPS, AAMAS, ICRA, and IROS.Subbarao Kambhampati is a professor in the School of Computing & AI at Arizona State University. Kambhampati studies fundamental problems in planning and decision making, motivated in particular by the challenges of human-aware AI systems. He is a fellow of the Association for the Advancement of Artificial Intelligence, the American Association for the Advancement of Science, and the Association for Computing Machinery, and was an NSF Young Investigator. He was the president of the Association for the Advancement of Artificial Intelligence, trustee of the International Joint Conference on Artificial Intelligence, and a founding board member of Partnership on AI. Kambhampati’s research, as well as his views on the progress and societal impacts of AI, have been featured in multiple national and international media outlets.