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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
16 years 1 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
16 years 1 months ago
GAMA (genetic algorithm driven multi-agents)for e-commerce integrative negotiation
Software agents help automate a variety of tasks including those involved in buying and selling products over the internet. The need for handling complex highly configurable produ...
Magda Bahaa Eldin Fayek, Ihab A. Talkhan, Khalil S...
GECCO
2009
Springer
152views Optimization» more  GECCO 2009»
16 years 1 months ago
Application of evolutionary algorithms in detection of SIP based flooding attacks
The Session Initiation Protocol (SIP) is the de facto standard for user’s session control in the next generation Voice over Internet Protocol (VoIP) networks based on the IP Mul...
M. Ali Akbar, Muddassar Farooq
GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
16 years 1 months ago
Analyzing the landscape of a graph based hyper-heuristic for timetabling problems
Hyper-heuristics can be thought of as “heuristics to choose heuristics”. They are concerned with adaptively finding solution methods, rather than directly producing a solutio...
Gabriela Ochoa, Rong Qu, Edmund K. Burke
GECCO
2009
Springer
16 years 1 months ago
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
In this paper, we rigorously analyse how the magnitude and frequency of change may affect the performance of the algorithm (1+1) EAdyn on a set of artificially designed pseudo-Bo...
Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
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