1325 search results - page 52 / 265 » Algorithm Selection using Reinforcement Learning |
104
click to vote
NIPS
1996
15 years 3 months ago
1996
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
79
Voted
ICPR
2006
IEEE
16 years 3 months ago
2006
IEEE
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
121
click to vote
ICRA
2009
IEEE
15 years 9 months ago
2009
IEEE
— Our goal in this work is to make high level decisions for mobile robots. In particular, given a queue of prioritized object delivery tasks, we wish to find a sequence of actio...
139
click to vote
ALT
2006
Springer
15 years 11 months ago
2006
Springer
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
194
click to vote
GECCO
2011
Springer
14 years 5 months ago
2011
Springer
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...