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ICRA
2002
IEEE
106views Robotics» more  ICRA 2002»
9 years 5 months ago
Stochastic Mapping Frameworks
— 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...
AAAI
1992
9 years 1 months ago
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
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. ...
BMCBI
2006
111views more  BMCBI 2006»
9 years 5 days ago
SIMMAP: Stochastic character mapping of discrete traits on phylogenies
Background: Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very ...
Jonathan P. Bollback
JC
2010
95views more  JC 2010»
8 years 10 months ago
Stochastic perturbations and smooth condition numbers
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...
Diego Armentano
ICML
2000
IEEE
10 years 28 days ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
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...
Michael H. Bowling
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