04.01.16 - 08.01.16, Seminar 16011

Evolution and Computing

Diese Seminarbeschreibung wurde vor dem Seminar auf unseren Webseiten veröffentlicht und bei der Einladung zum Seminar verwendet.


Biological evolution has produced an extraordinary diversity of organisms, even the simplest of which is highly adapted, with multiple complex structures. Dynamic structures at even higher levels emerge from collective and social behaviour. These phenomena have traditionally been studied in population genetics, ecology and related disciplines.

However, theoretical computer scientists, endowed with a wide variety of tools, have recently made progress in describing and characterising the computational capabilities of evolution, analyzing natural algorithms, obtaining quantitative bounds for evolutionary models and understanding the role of sex in evolution. The field of evolutionary computation has found that many innovative solutions to optimisation and design problems can be achieved by simulating living processes, such as evolution via random variation and selection, or social behaviour in insects. Researchers in evolutionary computation have recently started applying techniques from theoretical computer science to analyze the optimization time of natural algorithms.

While many connections and results spawned, much remains to be done. The goal of this seminar is to bring together this interdisciplinary group of researchers to further the connections and consolidate this burgeoning new discipline. Some of the general themes/questions that would be discussed are:

  • Could computational complexity and/or learning theory explain fundamental questions regarding the emergence of complexity in evolution and the origins of life?
  • Could we explain the efficacy of some of the algorithms found in nature and/or be inspired by such algorithms to design novel algorithms for classical problems?
  • Could we understand phase transitions and mixing times for important models of evolution/population genetics rigorously?
  • Could various dynamics in evolutionary biology (such as sexual evolution) be viewed as an optimization process and their equilibria studied from the lens of game theory?

Following the Dagstuhl tradition, the format of the seminar is intentionally loose. We propose to schedule a plenary session on the first day with introductory talks on the topics above followed by discussions, and identification of promising directions. The remaining of the seminar will consist of breakout sessions giving time for smaller groups to discuss specific problems in depth. The seminar will be concluded with a plenary wrap up session.