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IJCAI
1997
15 years 8 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
AAAI
2007
15 years 9 months ago
Knowledge-Driven Learning and Discovery
The goal of our current research is machine learning with the help and guidance of a knowledge base (KB). Rather than learning numerical models, our approach generates explicit sy...
Benjamin Lambert, Scott E. Fahlman
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
16 years 1 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
NAACL
2007
15 years 8 months ago
Comparing User Simulation Models For Dialog Strategy Learning
This paper explores what kind of user simulation model is suitable for developing a training corpus for using Markov Decision Processes (MDPs) to automatically learn dialog strate...
Hua Ai, Joel R. Tetreault, Diane J. Litman
NIPS
2004
15 years 8 months ago
Learning Preferences for Multiclass Problems
Many interesting multiclass problems can be cast in the general framework of label ranking defined on a given set of classes. The evaluation for such a ranking is generally given ...
Fabio Aiolli, Alessandro Sperduti