This letter discusses the recent paper "Some technical remarks on the proof of the 'No Free Lunch' theorem," In that paper, some technical issues related to the formal proof of the no free lunch (NFL) theorem for search were given by Wolpert and Macready (1995 and 1997). As a result of a discussion among the authors, this letter explores the issues raised in that paper more thoroughly. This includes the presentation of a simpler version of the NFL proof in accord with a suggestion made explicitly by Koppen (2000) and implicitly by Wolpert and Macready (1997). It also includes the correction of an incorrect claim made by Koppen (2000) of a limitation of the NFL theorem. Finally, some thoughts on future research directions for research into a...
The No Free Lunch theorem (NFL) asks some serious questions to researchers interested in search pr...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
Abstract — The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/s...
The No Free Lunch (NFL) theorem for search and optimisation states that averaged across all possible...
The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/search algor...
[...] Thus not only our reason fails us in the discovery of the ultimate connexion of causes and eff...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
A sizable amount of research has been done to improve the mechanisms for knowledge extraction such a...
The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in alg...
Wolpert and Macready’s No Free Lunch theorem proves that no search algorithm is better than any othe...
International audienceThis paper analyses extensions of No-Free-Lunch (NFL) theorems to countably in...
AbstractThe No Free Lunch (NFL) theorem due to Wolpert and Macready (IEEE Trans. Evol. Comput. 1(1) ...
The No Free Lunch (NFL) theorem due to Wolpert and Macready (1997) has led to controversial discussi...
The No Free Lunch theorem (NFL) asks some serious questions to researchers interested in search pr...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
Abstract — The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/s...
The No Free Lunch (NFL) theorem for search and optimisation states that averaged across all possible...
The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/search algor...
[...] Thus not only our reason fails us in the discovery of the ultimate connexion of causes and eff...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
A sizable amount of research has been done to improve the mechanisms for knowledge extraction such a...
The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in alg...
Wolpert and Macready’s No Free Lunch theorem proves that no search algorithm is better than any othe...
International audienceThis paper analyses extensions of No-Free-Lunch (NFL) theorems to countably in...
AbstractThe No Free Lunch (NFL) theorem due to Wolpert and Macready (IEEE Trans. Evol. Comput. 1(1) ...
The No Free Lunch (NFL) theorem due to Wolpert and Macready (1997) has led to controversial discussi...
The No Free Lunch theorem (NFL) asks some serious questions to researchers interested in search pr...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...