This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom.
As the population ages, the need grows for AI agents to assist people to remain living independently. Older adults are typically set in their ways, so AI agents should adapt to their ways of doing things, rather than the other way around. To that end, we are exploring various approaches to learning to personalize assistive agents, including the use of bandit algorithms, foundational models, neuro-symbolic architectures, and theory of mind. This talk will present our approaches and results in several assistive areas, including meal preparation and exercise coaching, as well as work in learning policies from humans. Much of the research is being supported by AI-CARING, an NSF-sponsored Institute devoted to developing AI technologies to help older adults with cognitive and physical decline remain in their homes.