272 search results - page 16 / 55 » Parallel Reinforcement Learning with Linear Function Approxi... |
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
ICML
1996
IEEE
14 years 8 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
AAAI
2006
13 years 9 months ago
2006
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
NIPS
1998
13 years 8 months ago
1998
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...