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Towards Large-Scale Optimization of Iterated Prisoner Dilemma Strategies

  • Grażyna Starzec
  • Mateusz Starzec
  • Aleksander ByrskiEmail author
  • Marek Kisiel-Dorohinicki
  • Juan C. Burguillo
  • Tom Lenaerts
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11370)

Abstract

The Iterated Prisoner’s Dilemma (IPD) game is a one of the most popular subjects of study in game theory. Numerous experiments have investigated many properties of this game over the last decades. However, topics related to the simulation scale did not always play a significant role in such experimental work. The main contribution of this paper is the optimization of IPD strategies performed in a distributed actor-based computing and simulation environment. Besides showing the scalability and robustness of the framework, we also dive into details of some key simulations, analyzing the most successful strategies obtained.

Keywords

Iterated prisoner dilemma Parallel simulation Optimization 

Notes

Acknowledgment

This research was supported by AGH University of Science and Technology Statutory Project.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Grażyna Starzec
    • 1
  • Mateusz Starzec
    • 1
  • Aleksander Byrski
    • 1
    Email author
  • Marek Kisiel-Dorohinicki
    • 1
  • Juan C. Burguillo
    • 2
  • Tom Lenaerts
    • 3
    • 4
  1. 1.Department of Computer ScienceAGH University of Science and TechnologyKrakowPoland
  2. 2.Escuela de Ingeniería de Telecomunicación, Campus Universitario Lagoas-MarcosendeUniversity of VigoVigoSpain
  3. 3.Machine Learning GroupUniversité Libre de BruxellesBrusselsBelgium
  4. 4.Artificial Intelligence LaboratoryVrije Universiteit BrusselBrusselsBelgium

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