241 search results - page 37 / 49 » Parameter learning for relational Bayesian networks |
ICRA
2009
IEEE
15 years 4 months ago
2009
IEEE
— In this paper, we present an approach that allows a robot to observe, generalize, and reproduce tasks observed from multiple demonstrations. Motion capture data is recorded in ...
DAGM
2007
Springer
15 years 1 months ago
2007
Springer
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
ML
1998
ACM
14 years 9 months ago
1998
ACM
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
NIPS
1998
14 years 11 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
WIOPT
2010
IEEE
14 years 8 months ago
2010
IEEE
—The paper presents a methodology that combines statistical learning with constraint optimization by locally optimizing Radio Resource Management (RRM) or system parameters of po...