Differential Evolution in Agent-Based Computing

  • Mateusz GodzikEmail author
  • Bartlomiej Grochal
  • Jakub Piekarz
  • Mikolaj Sieniawski
  • Aleksander ByrskiEmail author
  • Marek Kisiel-Dorohinicki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11432)


Evolutionary multi-agent systems (EMAS) turned out to be quite efficient technique for solving complex problems, both benchmark ones (as well-known multi-dimensional functions, e.g. Rastrigin, Schwefel etc) and more practical ones (like Optimal Golomb Ruler or Low Autocorrelation Binary Sequence). However the already classic design of the EMAS (these metaheuristics have been developed for over 15 years) has still many places for improvement. Hybridization is one of such means, and it turns out that incorporating Differential Evolution mechanisms into EMAS (altering the reproduction strategy by making it more social-aware) improves the accuracy of the search. This paper deals with discussion of selected means for hybridization of EMAS with DE, and provides an insight into the efficacy of the novel algorithm compared with classic techniques based on multidimensional benchmark problems.


Metaheuristics Agent-based computing Differential evolution Hybrid algorithms 



The research presented in this paper was supported by the funds assigned by the Polish Minister of Science and Higher Education to AGH University of Science and Technology.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mateusz Godzik
    • 1
    Email author
  • Bartlomiej Grochal
    • 1
  • Jakub Piekarz
    • 1
  • Mikolaj Sieniawski
    • 1
  • Aleksander Byrski
    • 1
    Email author
  • Marek Kisiel-Dorohinicki
    • 1
  1. 1.Department of Computer Science, Faculty of Computer Science, Electronics and TelecommunicationsAGH University of Science and TechnologyKrakówPoland

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