51 search results - page 9 / 11 » Characterizing reinforcement learning methods through parame... |
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
CP
2006
Springer
13 years 9 months ago
2006
Springer
The paper presents a method for generating solutions of a constraint satisfaction problem (CSP) uniformly at random. The main idea is to express the CSP as a factored probability d...
DSP
2006
13 years 5 months ago
2006
This paper considers the problem of sensor scheduling for the purposes of detection and tracking of "smart" targets. Smart targets are targets that can detect when they ...
NETCOOP
2007
Springer
13 years 12 months ago
2007
Springer
Recently Gerald Ash has shown through case studies that event dependent routing is attractive in large scale multi-service MPLS networks. In this paper, we consider the application...
GECCO
2005
Springer
13 years 11 months ago
2005
Springer
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...