THEORY - Theory
Description
The theory track welcomes all papers performing theoretical analyses or concerning theoretical aspects in evolutionary computation and related areas. Results can be proven with mathematical rigor or obtained via a thorough experimental investigation.
In addition to traditional areas in evolutionary computation like Genetic and Evolutionary Algorithms, Evolutionary Strategies, and Genetic Programming we also highly welcome theoretical papers in Artificial Life, Ant Colony Optimization, Swarm Intelligence, Estimation of Distribution Algorithms, Generative and Developmental Systems, Evolutionary Machine Learning, Search Based Software Engineering, Population Genetics, and more.
Scope
Topics include (but are not limited to):
- analytical methods like drift analysis, fitness levels, Markov chains, large deviation bounds,
- dynamic and static parameter choices,
- fitness landscapes and problem difficulty,
- population dynamics,
- problem representation,
- runtime analysis, black-box complexity, and alternative performance measures,
- single- and multi-objective problems,
- statistical approaches,
- stochastic and dynamic environments,
- variation and selection operators.
Papers submitted to the theory track may contain an appendix to give additional information. The appendix will not be part of the proceedings, and is consulted only at the discretion of the program committee. All technical details necessary for a proper evaluation must be contained in the 8-page submission or in the appendix, including full proofs and/or complete descriptions of experiments.
Track Chairs
Dirk Sudholt
University of Passau, Germany | webpage
Dirk Sudholt is a Full Professor and Chair of Algorithms for Intelligent Systems at the University of Passau, Germany. Before joining Passau, he was a Senior Lecturer at the University of Sheffield, UK, where he founded and led the Algorithms Research Group. He received his PhD in Computer Science from TU Dortmund, Germany, in 2008, under the supervision of Prof. Ingo Wegener. His research focuses on the computational complexity of randomised search heuristics such as evolutionary algorithms and estimation-of-distribution algorithms. In particular, his work includes runtime analysis of parallel evolutionary algorithms, diversity mechanisms, multi-objective optimisation and the benefits of crossover in genetic algorithms. Dirk has served as Co-Chair of FOGA 2017, Co-Chair of the GECCO Theory track in 2016, 2017, and 2025, and as Guest Editor for Algorithmica. He is a member of the Editorial Board of Evolutionary Computation and an Associate Editor for Natural Computing. He has authored 150 refereed publications and has received 12 best paper awards at GECCO and PPSN.Pietro S. Oliveto
Southern University of Science and Technology (SUSTech), China
Pietro S. Oliveto is a Professor of Computer Science and Head of the Theory of Artificial Intelligence Lab at the Southern University of Science and Technology (SUSTech), Shenzhen, China. He received the Laurea degree and PhD degree in computer science respectively from the University of Catania, Italy in 2005 and from the University of Birmingham, UK in 2009. He has been EPSRC PhD+ Fellow (2009-2010) and EPSRC Postdoctoral Fellow (2010-2013) at Birmingham and Vice-Chancellor's Fellow (2013-2016) and EPSRC Early Career Fellow at the University of Sheffield, UK (2015-2020).
His main research interest is the performance analysis of bio-inspired computation techniques including evolutionary algorithms, genetic programming, artificial immune systems, hyper-heuristics and algorithm configuration. He has guest-edited journal special issues of Computer Science and Technology, Evolutionary Computation, Theoretical Computer Science, IEEE Transactions on Evolutionary Computation and Algorithmica. He has co-Chaired the the IEEE symposium on Foundations of Computational Intelligence (FOCI) from 2015 to 2021 and has been co-program Chair of the ACM Conference on Foundations of Genetic Algorithms (FOGA 2021) and Theory Track co-chair at GECCO 2022 and GECCO 2023. He is part of the Steering Committee of the annual workshop on Theory of Randomized Search Heuristics (ThRaSH), and has been Leader of the Benchmarking Working Group of the COST Action ImAppNIO, member of the EPSRC Peer Review College and Associate Editor of IEEE Transactions on Evolutionary Computation.