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GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 10 months ago
Canonical representation genetic programming
Search spaces sampled by the process of Genetic Programming often consist of programs which can represent a function in many different ways. Thus, when the space is examined it i...
John R. Woodward, Ruibin Bai
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
15 years 10 months ago
Why evolution is not a good paradigm for program induction: a critique of genetic programming
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...
John R. Woodward, Ruibin Bai
GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
15 years 10 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
138views Optimization» more  GECCO 2009»
15 years 10 months ago
IMAD: in-execution malware analysis and detection
The sophistication of computer malware is becoming a serious threat to the information technology infrastructure, which is the backbone of modern e-commerce systems. We, therefore...
Syed Bilal Mehdi, Ajay Kumar Tanwani, Muddassar Fa...
GECCO
2009
Springer
156views Optimization» more  GECCO 2009»
15 years 10 months ago
Articulating user preferences in many-objective problems by sampling the weighted hypervolume
The hypervolume indicator has become popular in recent years both for performance assessment and to guide the search of evolutionary multiobjective optimizers. Two critical resear...
Anne Auger, Johannes Bader, Dimo Brockhoff, Eckart...