Towards Evolutionary Emergence

Bremer, Jörg; Lehnhoff, Sebastian

doi:10.15439/2021F111

Artykuł - szczegóły

Tytuł artykułu

Towards Evolutionary Emergence

Autorzy

Bremer Jörg , Lehnhoff Sebastian

Wybrane pełne teksty z tego czasopisma

http://annals-csis.org

Identyfikatory

DOI

10.15439/2021F111

Warianty tytułu

Konferencja

Federated Conference on Computer Science and Information Systems (16 ; 02-05.09.2021 ; online)

Języki publikacji

Abstrakty

With the upcoming era of large-scale, complex cyber-physical systems, also the demand for decentralized and self-organizing algorithms for coordination rises. Often such algorithms rely on emergent behavior; local observations and decisions aggregate to some global behavior without any apparent, explicitly programmed rule. Systematically designing these algorithms targeted for a new orchestration or optimization task is, at best, tedious and error prone. Suitable and widely applicable design patterns are scarce so far. We opt for a machine learning based approach that learns the necessary mechanisms. for targeted emergent behavior automatically. To achieve this, we use Cartesian genetic programming. As an example that demonstrates the general applicability of this idea, we trained a swarm-based optimization heuristics and present first results showing that the learned swarm behavior is significantly better than just random search. We also discuss the encountered pitfalls and remaining challenges on the research agenda.

Słowa kluczowe

cyber-physical systems self-organizing coordination machine learning

systemy cyberfizyczne samoorganizacja koordynacja uczenie maszynowe

Wydawca

Polskie Towarzystwo Informatyczne

Czasopismo

Annals of Computer Science and Information Systems

Rocznik

2021

Tom

Vol. 26

Strony

55--60

Opis fizyczny

Bibliogr. 59 poz., tab., rys.

Twórcy

autor

Bremer Jörg

joerg.bremer@uni-oldenburg.de

Department of Computing Science, Carl von Ossietzky University, Oldenburg, Germany

autor

Lehnhoff Sebastian

sebastian.lehnhoff@uni-oldenburg.de

Department of Computing Science, Carl von Ossietzky University, Oldenburg, Germany

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Uwagi

1. Preface

2. Session: 14th International Workshop on Computational Optimization

3. Communication Papers

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-16a2ed67-b96c-4efe-a91b-9ba9b2818d80