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CIMCA
2005
IEEE
15 years 9 months ago
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
98
Voted
CEEMAS
2003
Springer
15 years 8 months ago
Towards Autonomy, Self-Organisation and Learning in Holonic Manufacturing
This paper intends to discuss self-organisation and learning capabilities in autonomous and cooperative holons that are part of a holonic manufacturing control system. These capabi...
Paulo Leitão, Francisco Restivo
131
Voted
IJCAI
2007
15 years 5 months ago
Learning to Walk through Imitation
Programming a humanoid robot to walk is a challenging problem in robotics. Traditional approaches rely heavily on prior knowledge of the robot's physical parameters to devise...
Rawichote Chalodhorn, David B. Grimes, Keith Groch...
DAGSTUHL
2003
15 years 4 months ago
Maximizing Learning Progress: An Internal Reward System for Development
This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. It...
Frédéric Kaplan, Pierre-Yves Oudeyer
172
Voted
BC
2002
193views more  BC 2002»
15 years 3 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon