In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
In this paper, a new symmetry-based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. ...
The generation of better label placement configurations in maps is a problem that comes up in automated cartographic production. The objective of a good label placement is to displ...
Abstract— The problem of place recognition appears in different mobile robot navigation problems including localization, SLAM, or change detection in dynamic environments. Wherea...
In this work, we use points, lines, and the linear extremal contours of cylinders to estimate the position and orientation of the camera in the world coordinate system. Other line...