Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 22081)

Auger, Anne; Fonseca, Carlos M.; Friedrich, Tobias; Lengler, Johannes; Gissler, Armand

doi:10.4230/DagRep.12.2.87

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Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 22081)

Authors Anne Auger, Carlos M. Fonseca, Tobias Friedrich, Johannes Lengler, Armand Gissler and all authors of the abstracts in this report

Part of: Issue: Dagstuhl Reports, Volume 12, Issue 2
Part of: Volume: Dagstuhl Reports, Volume 12
Part of: Journal: Dagstuhl Reports (DagRep)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2022-08-23

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DagRep.12.2.87.pdf

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Document Identifiers

DOI: 10.4230/DagRep.12.2.87
URN: urn:nbn:de:0030-drops-169325

Author Details

Anne Auger

INRIA Saclay – Palaiseau, FR

Carlos M. Fonseca

University of Coimbra, PT

Tobias Friedrich

Hasso-Plattner-Institut, Universität Potsdam, DE

Johannes Lengler

ETH Zürich, CH

Armand Gissler

Ecole Polytechnique - Palaiseau, FR

and all authors of the abstracts in this report

Cite AsGet BibTex

Anne Auger, Carlos M. Fonseca, Tobias Friedrich, Johannes Lengler, and Armand Gissler. Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 22081). In Dagstuhl Reports, Volume 12, Issue 2, pp. 87-102, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/DagRep.12.2.87

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 22081 "Theory of Randomized Optimization Heuristics". This seminar is part of a biennial seminar series. This year, we focused on connections between classical topics of the community, such as Evolutionary Algorithms and Strategies (EA, ES), Estimation-of-Distribution Algorithms (EDA) and Evolutionary Multi-Objective Optimization (EMO), and related fields like Stochastic Gradient Descent (SGD) and Bayesian Optimization (BO). The mixture proved to be extremely successful. Already the first talk turned into a two hour long, vivid and productive plenary discussion. The seminar was smaller than previous versions (due to corona regulations), but its intensity more than made up for the smaller size.

Subject Classification

ACM Subject Classification

Theory of computation → Bio-inspired optimization
Theory of computation → Evolutionary algorithms
Theory of computation → Theory of randomized search heuristics

Keywords

black-box optimization
derivative-free optimization
evolutionary and genetic algorithms
randomized search algorithms
stochastic gradient descent
theoretical computer science

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