66 search results - page 11 / 14 » Bayesian Multi-Task Reinforcement Learning |
CL
2000
Springer
14 years 2 months ago
2000
Springer
In this paper I give a brief overview of recent work on uncertainty inAI, and relate it to logical representations. Bayesian decision theory and logic are both normative frameworks...
NIPS
1996
13 years 11 months ago
1996
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
PKDD
2009
Springer
14 years 4 months 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...
CSL
2010
Springer
13 years 10 months ago
2010
Springer
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
ICML
2008
IEEE
14 years 10 months ago
2008
IEEE
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...