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Combining Meta-EAs and Racing for Difficult EA Parameter Tuning Tasks
| Content Provider | CiteSeerX |
|---|---|
| Author | Yuan, Bo Gallagher, Marcus |
| Abstract | Summary. This chapter presents a novel framework for tuning the parameters of Evolutionary Algorithms. A hybrid technique combining Meta-EAs and statistical Racing approaches is developed, which is not only capable of effectively exploring the search space of numerical parameters but also suitable for tuning symbolic parameters where it is generally difficult to define any sensible distance metric. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Difficult Ea Parameter Tuning Task Search Space Hybrid Technique Sensible Distance Statistical Racing Approach Numerical Parameter Novel Framework Evolutionary Algorithm Symbolic Parameter |
| Content Type | Text |
| Resource Type | Article |