The No-Free-Lunch theorem is a fundamental result in the field of black-box function optimization. Recent work has shown that coevolution can exhibit free lunches. The question as to which classes of coevolution exhibit free lunches is still open. In this paper we present a novel framework for analyzing No-Free-Lunch like results for classes of coevolutionary algorithms. Our framework has the advantage of analyzing No-Free-Lunch like inquiries in terms of solution concepts and isomorphisms on the weak preference relation on solution configurations. This allows coevolutionary algorithms to be naturally classified by the type of solution they seek. Using the weak preference relation also permits us to present a simpler definition of performan...
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 (NFL) theorem for search and optimisation states that averaged across all possible...
Recent work in test based coevolution has focused on employing ideas from multi-objective optimizati...
The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in alg...
Abstract — The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/s...
Abstract — Recent work on the foundational underpinnings of black-box optimization has begun to unco...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
[...] Thus not only our reason fails us in the discovery of the ultimate connexion of causes and eff...
International audienceThis paper analyses extensions of No-Free-Lunch (NFL) theorems to countably in...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/search algor...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
This letter discusses the recent paper "Some technical remarks on the proof of the 'No Free Lunch' t...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
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 (NFL) theorem for search and optimisation states that averaged across all possible...
Recent work in test based coevolution has focused on employing ideas from multi-objective optimizati...
The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in alg...
Abstract — The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/s...
Abstract — Recent work on the foundational underpinnings of black-box optimization has begun to unco...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
[...] Thus not only our reason fails us in the discovery of the ultimate connexion of causes and eff...
International audienceThis paper analyses extensions of No-Free-Lunch (NFL) theorems to countably in...
It is often claimed that Evolutionary Algorithms are superior to other optimization techniques, in p...
The No-Free-Lunch (NFL) Theorem provides a fundamental limit governing all optimization/search algor...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
This letter discusses the recent paper "Some technical remarks on the proof of the 'No Free Lunch' t...
We extend previous results concerning Black-Box search algorithms, presenting new theoretical tools ...
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 (NFL) theorem for search and optimisation states that averaged across all possible...