18 search results - page 3 / 4 » Incremental Least Squares Policy Iteration for POMDPs |
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
ATAL
2009
Springer
13 years 12 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
AAAI
2010
13 years 6 months ago
2010
Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
ICMLA
2008
13 years 6 months ago
2008
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...