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SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
14 years 2 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
TEC
2010
132views more  TEC 2010»
13 years 2 months ago
A Hybrid Evolutionary Approach to the Nurse Rostering Problem
Nurse rostering is a difficult search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle t...
Ruibin Bai, Edmund K. Burke, Graham Kendall, Jingp...
IPPS
2003
IEEE
14 years 1 months ago
Agent-Based Grid Load Balancing Using Performance-Driven Task Scheduling
Load balancing is a key concern when developing parallel and distributed computing applications. The emergence of computational grids extends this problem, where issues of cross-d...
Junwei Cao, Daniel P. Spooner, Stephen A. Jarvis, ...
MM
2010
ACM
115views Multimedia» more  MM 2010»
13 years 6 months ago
Interactive learning of heterogeneous visual concepts with local features
In the context of computer-assisted plant identification we are facing challenging information retrieval problems because of the very high within-class variability and of the lim...
Wajih Ouertani, Michel Crucianu, Nozha Boujemaa
LCTRTS
1995
Springer
13 years 11 months ago
Scheduling of Hard Aperiodic Tasks in Hybrid Static/Dynamic Priority Systems
In this paper, we present a preemptive joint scheduling of hard deadline periodic and hard deadline aperiodic tasks on a uniprocessor real-time system. The scheduling has extended...
Jongwon Lee, Sungyoung Lee, Hyungill Kim