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DAC
2001
ACM
16 years 5 months ago
MetaCores: Design and Optimization Techniques
Currently, hardware intellectual property (IP) is delivered at vels of abstraction: hard, firm, and soft. In order to further enhance performance, efficiency, and flexibility of I...
Seapahn Meguerdichian, Farinaz Koushanfar, Advait ...
EMO
2006
Springer
161views Optimization» more  EMO 2006»
15 years 7 months ago
Design Issues in a Multiobjective Cellular Genetic Algorithm
In this paper we study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. We take as an starting point an algorithm fol...
Antonio J. Nebro, Juan José Durillo, Franci...
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 10 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...
ESA
2010
Springer
183views Algorithms» more  ESA 2010»
15 years 5 months ago
Spatio-temporal Range Searching over Compressed Kinetic Sensor Data
As sensor networks increase in size and number, efficient techniques are required to process the very large data sets that they generate. Frequently, sensor networks monitor object...
Sorelle A. Friedler, David M. Mount
GECCO
2006
Springer
190views Optimization» more  GECCO 2006»
15 years 7 months ago
Design synthesis of microelectromechanical systems using genetic algorithms with component-based genotype representation
An automated design synthesis system based on a multi-objective genetic algorithm (MOGA) has been developed for the optimization of surface-micromachined MEMS devices. A hierarchi...
Ying Zhang, Raffi R. Kamalian, Alice M. Agogino, C...