298 search results - page 19 / 60 » Optimizing number of hidden neurons in neural networks |
AR
2007
13 years 8 months ago
2007
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
CEC
2007
IEEE
14 years 2 months ago
2007
IEEE
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demons...
IROS
2009
IEEE
14 years 2 months ago
2009
IEEE
— Fluid bipedal locomotion remains a significant challenge for humanoid robotics. Recent bio-inspired approaches have made significant progress by using small numbers of tightl...
ICANN
2009
Springer
14 years 15 days ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...