No strategy can win in the repeated prisoner’s dilemma: linking game theory and computer simulations.

Julian Garcia, Matthijs van Veelen

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Computer simulations are regularly used for studying the evolution of strategies in repeated games. These simulations rarely pay attention to game theoretical results that can illuminate the data analysis or the questions being asked. Results from evolutionary game theory imply that for every Nash equilibrium, there are sequences of mutants that would destabilize them. If strategies are not limited to a finite set, populations move between a variety of Nash equilibria with different levels of cooperation. This instability is inescapable, regardless of how strategies are represented. We present algorithms that show that simulations do agree with the theory. This implies that cognition itself may only have limited impact on the cycling dynamics. We argue that the role of mutations or exploration is more important in determining levels of cooperation.
LanguageEnglish
Article number102
Number of pages14
JournalFrontiers in Robotics and AI
Volume5
DOIs
Publication statusPublished - 29 Aug 2018

Cite this

@article{eb66d68669b84da6ad6c6a4816c567ad,
title = "No strategy can win in the repeated prisoner’s dilemma: linking game theory and computer simulations.",
abstract = "Computer simulations are regularly used for studying the evolution of strategies in repeated games. These simulations rarely pay attention to game theoretical results that can illuminate the data analysis or the questions being asked. Results from evolutionary game theory imply that for every Nash equilibrium, there are sequences of mutants that would destabilize them. If strategies are not limited to a finite set, populations move between a variety of Nash equilibria with different levels of cooperation. This instability is inescapable, regardless of how strategies are represented. We present algorithms that show that simulations do agree with the theory. This implies that cognition itself may only have limited impact on the cycling dynamics. We argue that the role of mutations or exploration is more important in determining levels of cooperation.",
author = "Julian Garcia and {van Veelen}, Matthijs",
year = "2018",
month = "8",
day = "29",
doi = "10.3389/frobt.2018.00102",
language = "English",
volume = "5",
journal = "Frontiers in Robotics and AI",
issn = "2296-9144",
publisher = "Frontiers Media",

}

No strategy can win in the repeated prisoner’s dilemma : linking game theory and computer simulations. / Garcia, Julian; van Veelen, Matthijs.

In: Frontiers in Robotics and AI, Vol. 5, 102, 29.08.2018.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - No strategy can win in the repeated prisoner’s dilemma

T2 - Frontiers in Robotics and AI

AU - Garcia, Julian

AU - van Veelen, Matthijs

PY - 2018/8/29

Y1 - 2018/8/29

N2 - Computer simulations are regularly used for studying the evolution of strategies in repeated games. These simulations rarely pay attention to game theoretical results that can illuminate the data analysis or the questions being asked. Results from evolutionary game theory imply that for every Nash equilibrium, there are sequences of mutants that would destabilize them. If strategies are not limited to a finite set, populations move between a variety of Nash equilibria with different levels of cooperation. This instability is inescapable, regardless of how strategies are represented. We present algorithms that show that simulations do agree with the theory. This implies that cognition itself may only have limited impact on the cycling dynamics. We argue that the role of mutations or exploration is more important in determining levels of cooperation.

AB - Computer simulations are regularly used for studying the evolution of strategies in repeated games. These simulations rarely pay attention to game theoretical results that can illuminate the data analysis or the questions being asked. Results from evolutionary game theory imply that for every Nash equilibrium, there are sequences of mutants that would destabilize them. If strategies are not limited to a finite set, populations move between a variety of Nash equilibria with different levels of cooperation. This instability is inescapable, regardless of how strategies are represented. We present algorithms that show that simulations do agree with the theory. This implies that cognition itself may only have limited impact on the cycling dynamics. We argue that the role of mutations or exploration is more important in determining levels of cooperation.

U2 - 10.3389/frobt.2018.00102

DO - 10.3389/frobt.2018.00102

M3 - Article

VL - 5

JO - Frontiers in Robotics and AI

JF - Frontiers in Robotics and AI

SN - 2296-9144

M1 - 102

ER -