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SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 6 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»
14 years 6 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
15 years 5 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»
14 years 10 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
15 years 3 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