76 search results - page 10 / 16 » Reinforcement Learning Based Neural Controllers for Dynamic ... |
GECCO
2009
Springer
14 years 3 days ago
2009
Springer
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
IAT
2010
IEEE
13 years 5 months ago
2010
IEEE
It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In t...
AAAI
2010
13 years 9 months ago
2010
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
ICCS
2007
Springer
14 years 1 months ago
2007
Springer
New architectures for Brain-Machine Interface communication and control use mixture models for expanding rehabilitation capabilities of disabled patients. Here we present and test ...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...