Name
Abstract | ||
|---|---|---|
We formalize the concept of an unbiased black box algorithm, which generalises the idea previously introduced by Lehre and Witt. Our formalization of bias relates to the symmetry group of the problem class under consideration, establishing a connection with previous work on No Free Lunch. Our definition is motivated and justified by a series of results, including the outcome that given a biased algorithm, there exists a corresponding unbiased algorithm with the same expected behaviour (over the problem class) and equal or better worst-case performance. For the case of evolutionary algorithms, it is already known how to construct unbiased mutation and crossover operators, and we summarise those results. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2001576.2001850 | GECCO |
Keywords | Field | DocType |
unbiased black box search,expected behaviour,crossover operator,corresponding unbiased algorithm,problem class,unbiased black box algorithm,evolutionary algorithm,previous work,symmetry group,free lunch,unbiased mutation,no free lunch,theory,combinatorial optimization,search algorithm | Black box (phreaking),Mathematical optimization,Crossover,Search algorithm,Existential quantification,Evolutionary algorithm,Computer science,No free lunch in search and optimization,Combinatorial optimization,Operator (computer programming),Artificial intelligence,Machine learning | Conference |
Citations | PageRank | References |
18 | 0.89 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan E. Rowe | 1 | 458 | 56.35 |
| Michael D. Vose | 2 | 752 | 215.67 |