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GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
13 years 10 months ago
Designing safe, profitable automated stock trading agents using evolutionary algorithms
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...
Harish Subramanian, Subramanian Ramamoorthy, Peter...
CEC
2010
IEEE
13 years 8 months ago
Providing a memory mechanism to enhance the evolutionary design of heuristics
Genetic programming approaches have previously been employed in the literature to evolve heuristics for various combinatorial optimisation problems. This paper presents a hyper-heu...
Edmund K. Burke, Matthew R. Hyde, Graham Kendall
ICDCS
2003
IEEE
14 years 9 days ago
Dynamic Module Replacement in Distributed Protocols
Dynamic module replacement — the ability to hot swap a component’s implementation at runtime — is fundamental to supporting evolutionary change in long-lived and highlyavail...
Nigamanth Sridhar, Scott M. Pike, Bruce W. Weide
GECCO
2003
Springer
14 years 7 days ago
Dynamic Maximum Tree Depth
We present a technique, designated as dynamic maximum tree depth, for avoiding excessive growth of tree-based GP individuals during the evolutionary process. This technique introdu...
Sara Silva, Jonas Almeida
GECCO
2003
Springer
182views Optimization» more  GECCO 2003»
14 years 7 days ago
Spatial Operators for Evolving Dynamic Bayesian Networks from Spatio-temporal Data
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
Allan Tucker, Xiaohui Liu, David Garway-Heath