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» Adapting RBF Neural Networks to Multi-Instance Learning
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IAT
2008
IEEE
13 years 7 months ago
Scaling Up Multi-agent Reinforcement Learning in Complex Domains
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
Dan Xiao, Ah-Hwee Tan
ESANN
2006
13 years 9 months ago
Magnification control for batch neural gas
Neural gas (NG) constitutes a very robust clustering algorithm which can be derived as stochastic gradient descent from a cost function closely connected to the quantization error...
Barbara Hammer, Alexander Hasenfuss, Thomas Villma...
AIIDE
2006
13 years 9 months ago
Incorporating Advice into Neuroevolution of Adaptive Agents
Neuroevolution is a promising learning method in tasks with extremely large state and action spaces and hidden states. Recent advances allow neuroevolution to take place in real t...
Chern Han Yong, Kenneth O. Stanley, Risto Miikkula...
ATAL
2006
Springer
13 years 11 months ago
Learning a common language through an emergent interaction topology
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Samarth Swarup, Kiran Lakkaraju, Les Gasser
AIIA
2001
Springer
14 years 4 days ago
A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...
Giovanna Castellano, Anna Maria Fanelli