35 search results - page 5 / 7 » Using evolution to improve neural network learning: pitfalls... |
GECCO
2010
Springer
13 years 11 months ago
2010
Springer
Multiobjective evolutionary algorithms have long been applied to engineering problems. Lately they have also been used to evolve behaviors for intelligent agents. In such applicat...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
ICANN
2009
Springer
14 years 9 days ago
2009
Springer
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
GECCO
2004
Springer
14 years 1 months ago
2004
Springer
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...