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» Learning a Generative Model for Structural Representations
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ITRE
2005
IEEE
15 years 5 months ago
Structure learning of Bayesian networks using a semantic genetic algorithm-based approach
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
Sachin Shetty, Min Song
ICRA
2002
IEEE
128views Robotics» more  ICRA 2002»
15 years 4 months ago
Generation of a Task Model by Integrating Multiple Observations of Human Demonstrations
This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
ATAL
2005
Springer
15 years 5 months ago
Generating intentions through argumentation
In this paper we consider how a BDI agent might determine its best course of action. We draw on previous work which has presented a model of persuasion over action and we discuss ...
Katie Atkinson, Trevor J. M. Bench-Capon, Peter Mc...
IJCNN
2007
IEEE
15 years 6 months ago
Adaptive Dynamic Modularity in a Connectionist Model of Context-Dependent Idea Generation
Abstract— Cognitive control - the ability to produce appropriate behavior in complex situations - is a fundamental aspect of intelligence. It is increasingly evident that this co...
Simona Doboli, Ali A. Minai, Vincent R. Brown
MLMI
2007
Springer
15 years 6 months ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...