Towards Large-Scale Optimization of Iterated Prisoner Dilemma Strategies

Grażyna Starzec, Mateusz Starzec, Aleksander Byrski, Marek Kisiel-Dorohinicki, Juan C. Burguillo, Tom Lenaerts

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publicationTransactions on computational collective intelligence XXXII
Subtitle of host publicationLecture Notes in Computer Science
PublisherSpringer Verlag
Pages167-183
Number of pages17
Volume11370
ISBN (Print)978-3-662-58611-2
DOIs
Publication statusPublished - 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11370 LNCS

Keywords

  • Iterated prisoner dilemma
  • Optimization
  • Parallel simulation

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