43 search results - page 4 / 9 » Training Reinforcement Neurocontrollers Using the Polytope A... |
GLOBECOM
2010
IEEE
13 years 5 months ago
2010
IEEE
Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
ICRA
2005
IEEE
14 years 1 months ago
2005
IEEE
— This paper presents a new reinforcement learning algorithm for accelerating acquisition of new skills by real mobile robots, without requiring simulation. It speeds up Q-learni...
EVOW
2008
Springer
13 years 8 months ago
2008
Springer
Abstract. This contribution studies speciation from the standpoint of evolutionary robotics (ER). A common approach to ER is to design a robot’s control system using neuro-evolut...
ICRA
2006
IEEE
14 years 1 months ago
2006
IEEE
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...