85 search results - page 4 / 17 » A Note on Learning and Evolution in Neural Networks |
JMLR
2008
13 years 6 months ago
2008
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
SEAL
1998
Springer
13 years 11 months ago
1998
Springer
This paper empirically investigates the use and behaviour of Evolution Strategies (ES) algorithms on problems such as function optimisation and the use of evolutionary artificial ...
ECAL
2001
Springer
13 years 11 months ago
2001
Springer
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
ECAL
2007
Springer
13 years 10 months ago
2007
Springer
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
GECCO
2005
Springer
14 years 7 days ago
2005
Springer
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...