— Stochastic mapping is an approach to the concurrent mapping and localization (CML) problem. The approach is powerful because feature and robot states are explicitly correlated....
Richard J. Rikoski, John J. Leonard, Paul M. Newma...
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
Thomas Dean, Dana Angluin, Kenneth Basye, Sean P. ...
Background: Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very ...
In this paper we dene a new condition number adapted to directionally uniform perturbations in a general framework of maps between Riemannian manifolds. The denitions and theorem...
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...