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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

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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. He previously held a post as Senior Lecturer at the University of Sheffield, UK, and founding head of the Algorithms research group. He obtained his PhD in computer science in 2008 from TU Dortmund, Germany, under the supervision of Prof. Ingo Wegener. His research focuses on the computational complexity of randomized search heuristics such as evolutionary algorithms and estimation-of-distribution algorithms. In particular, his work covered runtime analysis of parallel evolutionary algorithms, diversity mechanisms, multi-objective optimisation and the benefits of crossover in genetic algorithms. Dirk has served as chair of FOGA 2017, the GECCO Theory track in 2016 and 2017 and as guest editor for Algorithmica. He is a member of the editorial board of Evolutionary Computation and associate editor for Natural Computing. He has more than 130 refereed publications and won 10 best paper awards at GECCO and PPSN.

Pietro S. Oliveto

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