Future computing environments will free the user from the constraints of the desktop.
Applications for a mobile environment should take advantage of contextual information, such as …

This paper surveys locally weighted learning, a form of lazy learning and memory-based
learning, and focuses on locally weighted linear regression. The survey discusses distance …

We are building a home, called the Aware Home, to create a living laboratory for research in
ubiquitous computing for everyday activities. This paper introduces the Aware Home project …

We present a new algorithm,prioritized sweeping, for efficient prediction and control of
stochastic Markov systems. Incremental learning methods such as temporal differencing and Q-…

Unrestrained human arm trajectories between point targets have been investigated using a
three-dimensional tracking apparatus, the Selspot system. Movements were executed …

The goal of robot learning from demonstration is to have a robot learn from watching a
demonstration of the task to be performed. In our approach to learning from demonstration the …

Exoskeletons and active prostheses promise to enhance human mobility, but few have
succeeded. Optimizing device characteristics on the basis of measured human performance …

Lazy learning methods provide useful representations and training algorithms for learning
about complex phenomena during autonomous adaptive control of complex systems. This …

The inertial parameters of manipulator rigid-body loads and links have been automatically
estimated as a result of gen eral movement. The Newton-Euler equations have been recast to …

We introduce a constructive, incremental learning system for regression problems that models
data by means of spatially localized linear models. In contrast to other approaches, the …