Trajectory design for high-dimensional systems with nonconvex constraints is a challenging problem considered in this paper. Classical dynamic programming is often employed, but c...
We present a novel framework based on hidden Markov models (HMMs) for matching feature point sets, which capture the shapes of object contours of interest. Point matching algorith...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
: Heterogeneous wireless sensor networks represent a challenging programming environment. Servilla addresses this by offering a new middleware framework that provides service provi...
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...