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» Finding Structure in Reinforcement Learning
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163
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JMLR
2010
189views more  JMLR 2010»
14 years 10 months ago
Adaptive Step-size Policy Gradients with Average Reward Metric
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
Takamitsu Matsubara, Tetsuro Morimura, Jun Morimot...
143
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DPC
1996
192views more  DPC 1996»
15 years 4 months ago
Finding Pictures of Objects in Large Collections of Images
Retrieving images from very large collections, using image content as a key, is becoming an important problem. Users prefer to ask for pictures using notions of content that are st...
David A. Forsyth, Jitendra Malik, Thomas K. Leung,...
132
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GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
15 years 4 months ago
On the effects of node duplication and connection-oriented constructivism in neural XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull
ICML
2005
IEEE
16 years 4 months ago
New kernels for protein structural motif discovery and function classification
We present new, general-purpose kernels for protein structure analysis, and describe how to apply them to structural motif discovery and function classification. Experiments show ...
Chang Wang, Stephen D. Scott
157
Voted
HCW
1999
IEEE
15 years 8 months ago
Multiple Cost Optimization for Task Assignment in Heterogeneous Computing Systems Using Learning Automata
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Raju D. Venkataramana, N. Ranganathan