22 search results - page 1 / 5 » Tighter Value Function Bounds for Bayesian Reinforcement Lea... |
PKDD
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
ICAART
2010
INSTICC
14 years 2 months ago
2010
INSTICC
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
CORR
2012
Springer
12 years 1 months ago
2012
Springer
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
PKDD
2009
Springer
14 years 6 days ago
2009
Springer
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...