More Precise Runtime Analyses of Non-elitist Evolutionary Algorithms in Uncertain Environments
Work
Year: 2022
Type: article
Abstract: Real-world applications often involve “uncertain” objectives, i.e., where optimisation algorithms observe objective values as a random variables with positive variance. In the past decade, several ri... more
Source: Algorithmica
Authors Per Kristian Lehre, Xiaoyu Qin
Institution University of Birmingham
Cites: 54
Cited by: 3
Related to: 10
FWCI: 0.433
Citation percentile (by year/subfield): 80.94
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
APC paid (est): $2,890
Funder Alan Turing Institute
Grant ID EP/V025562/1