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» Learning for Dynamic Subsumption
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ICML
2009
IEEE
15 years 6 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
15 years 6 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
NIPS
1996
15 years 1 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
APSCC
2008
IEEE
15 years 6 months ago
Adaptive Learning Sequencing for Course Customization: A Web Service Approach
— We discuss a learning model that enables the creation of optimal learning strategies that suit learners’ needs. A customized learning content is delivered to learners as mana...
Ivan Madjarov, Abdelkader Bétari
TEC
2008
165views more  TEC 2008»
14 years 11 months ago
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
Shengxiang Yang, Xin Yao