This paper describes relationships among home and community environmental features, activity performance in the home, and community participation potential to support aging in place. A subset of data on older adults with functional limitations (N = 122), sixty three (63) with mobility and 59 with other limitations, were utilized in this study from a larger project's subject pool. Results showed significant and positive correlations between environmental barriers, activity dependence and difficulty at home, and less community participation in the mobility limitation group. While kitchen and bathroom features were most limiting to home performance, bathtub or shower was the only home feature, and destination social environment was the only community feature, that explained community participation. Compared to environmental features, home performance explained much more community participation. Study results provide detailed information about environmental features as well as types of home activities that can be prioritized as interventions for aging in place.
This paper presents an approach to assist the generation of agent-based cooperative animation using reinforcement learning. We focus on manipulation skills for box-shaped objects, including pushing, pulling, and moving objects in a relay way. There are a learning process and an animation process. In the learning process, different kinds of agents are trained using reinforcement learning. Policies are learned to control the agents to perform specific tasks. A physics simulator is adopted to simulate the interaction among objects. In the animation process, users animate agents with the learned policies. We propose several tools to intuitively create cooperative animations. We applied our method to generate several animations in which agents work together to finish tasks. A user study indicates that by using our tools, diverse cooperative animations can be easily created.
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