99 search results - page 13 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
NIPS
2003
13 years 9 months ago
2003
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
ITS
2004
Springer
14 years 1 months ago
2004
Springer
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
ECAI
2010
Springer
13 years 8 months ago
2010
Springer
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
ICRA
2007
IEEE
14 years 1 months ago
2007
IEEE
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...