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» Combining Learned Discrete and Continuous Action Models
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NIPS
2003
15 years 5 months ago
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
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...
Marc Toussaint
EVOW
2009
Springer
15 years 11 months ago
Evolutionary Optimization Guided by Entropy-Based Discretization
The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Guleng Sheri, David W. Corne
CEC
2003
IEEE
15 years 7 months ago
Playing in continuous spaces: some analysis and extension of population-based incremental learning
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
Bo Yuan, Marcus Gallagher
JMLR
2010
119views more  JMLR 2010»
14 years 11 months ago
The Coding Divergence for Measuring the Complexity of Separating Two Sets
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
Mahito Sugiyama, Akihiro Yamamoto
IBPRIA
2007
Springer
15 years 10 months ago
HMM-Based Action Recognition Using Contour Histograms
This paper describes an experimental study about a robust contour feature (shape-context) for using in action recognition based on continuous hidden Markov models (HMM). We ran dif...
Maria Ángeles Mendoza, Nicolas Pérez...