135 search results - page 23 / 27 » Solving the Ill-Conditioning in Neural Network Learning |
NPL
2000
14 years 9 months ago
2000
In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future...
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
AR
2007
14 years 9 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...
ECAL
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
NN
2002
Springer
14 years 9 months ago
2002
Springer
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...