The world's population is growing older; it is estimated that in 2050 there will be three times more people over the age 85 than there are today. Many are expected to need physical and cognitive assistance, and all will need additional healthcare. Shortages in primary care physicians, nurses, and managed care facility space and staff are already an issue today, creating a niche for assistive technologies to fill the care gap. A growing body of research shows that certain behavior patterns have a positive impact on longevity and wellness, including regular physical exercise, social interaction, and cognitive engagement. This project aims to develop and evaluate socially assistive human-machine interaction techniques that influence the user to engage in and comply with wellness-promoting behaviors in the home or nursing home in order to enhance longevity and quality of life. This work is focused on developing socially assistive systems (SAS) using peer-level human-machine interaction in which the machine serves in the role of a knowledgeable embodied agent capable of providing time-extended, sustained, and engaging interaction. The research focuses on two types of wellness-promoting human-machine interactions: 1) exercise sessions (cognitive and/or physical) and 2) socializing sessions. For one-on-one exercise sessions, the project is developing SAS capabilities that provide exercise monitoring, coaching, and motivation. For socialization, the research is developing SAS capabilities that provide social interaction and friendly reminders and encouragement to comply with health regimens (taking medicine, being physically active) and healthy habits (calling family, meeting friends). The two types of interactions share the common goal of influencing human behavior, and the main contribution of the research is the set of methods and algorithms for influencing behavior though human-machine interaction. This is achieved through a novel two-fold approach: 1) adaptive interaction steering for short-term interactions, and 2) motivation and coaching of behavior in longer-term interactions to maintain engagement and enhance task performance. The embodiment of the SAS is leveraged to maximize engagement and compliance; a key focus of the work is on developing a comprehensive method for natural, persuasive and engaging embodied communication. The methods and algorithms being developed are general, and will be implemented and tested on both computer-based and robot-based agents. In this way the work validates the developed methods on multiple technology platforms and embodiments, and compares their relative effectiveness and acceptability by the intended user population. The specifics of the implementation are informed by an early focus group with elderly participants, the target user population. The developed techniques are being implemented in both human-computer interaction (HCI) and human-robot interaction (HRI) versions, and are being evaluated with a large group of elderly users interacting with the SAS implementations over a multi-week user study. The work is focused on generating methods, algorithms, and a large corpus of multi-modal data (video, audio, and questionnaires) for grounding continued research into health and wellness-relevant HRI and HCI. This project aims to address a component of the nationally recognized healthcare challenge of promoting wellness and longevity in the aging population. Beyond basic algorithm and method development, the project implements and tests real-world socially assistive systems, both computer-based and robot-based, with a large population of elderly retirement home residents. The project is expected to produce insights useful for both research and healthcare product development for addressing this growing segment of the population. In addition to the socially relevant research focus, the project team is also engaged in a comprehensive program of K-12 outreach activities, which use robotics to promote STEM topic learning using the health theme of the proposal. The project involves inner city K-12 teachers and students in annual open houses, assemblies, and workshops that provide hands-on experiences with assistive systems for the elderly, as well as take-home materials for continued learning. The project team includes PhD students, undergraduates, and K-12 volunteers, and establishes a mentoring pipeline so that university students are both mentored and serve as mentors and role models for their younger peers.