English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Evolutionary Successful Strategies in a Transparent iterated Prisoner’s Dilemma

Unakafov, A. M., Schultze, T., Kagan, I., Moeller, S., Gail, A., Treue, S., et al. (2019). Evolutionary Successful Strategies in a Transparent iterated Prisoner’s Dilemma. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: Lecture Notes in Computer Science (pp. 204-219). Cham: Springer International Publishing. doi:10.1007/978-3-030-16692-2_14.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Unakafov, Anton M.1, Author           
Schultze, Thomas, Author
Kagan, Igor, Author
Moeller, Sebastian, Author
Gail, Alexander, Author
Treue, Stefan, Author
Eule, Stephan2, Author           
Wolf, Fred1, Author           
Affiliations:
1Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063289              
2Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063286              

Content

show
hide
Free keywords: -
 Abstract: A Transparent game is a game-theoretic setting that takes
action visibility into account. In each round, depending on the relative timing of their actions, players have a certain probability to see their partner’s choice before making their own decision. This probability is determined by the level of transparency. At the two extremes, a game with zero
transparency is equivalent to the classical simultaneous game, and a game
with maximal transparency corresponds to a sequential game. Despite the
prevalence of intermediate transparency in many everyday interactions
such scenarios have not been sufficiently studied. Here we consider a transparent iterated Prisoner’s dilemma (iPD) and use evolutionary simulations to investigate how and why the success of various strategies changes
with the level of transparency.We demonstrate that non-zero transparency
greatly reduces the set of successful memory-one strategies compared to
the simultaneous iPD. For low and moderate transparency the classical
“Win - Stay, Lose - Shift” (WSLS) strategy is the only evolutionary successful strategy. For high transparency all strategies are evolutionary unstable
in the sense that they can be easily counteracted, and, finally, for maximal
transparency a novel “Leader-Follower” strategy outperforms WSLS. Our
results provide a partial explanation for the fact that the strategies proposed for the simultaneous iPD are rarely observed in nature, where high
levels of transparency are common.

Details

show
hide
Language(s):
 Dates: 2019-03-302019
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-030-16692-2_14
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Applications of Evolutionary Computation: Lecture Notes in Computer Science
Source Genre: Book
 Creator(s):
Kaufmann, Paul1, Editor
Castillo, Pedro A.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Cham : Springer International Publishing
Pages: - Volume / Issue: 11454 Sequence Number: - Start / End Page: 204 - 219 Identifier: ISSN: 0302-9743
ISSN: 1611-3349
ISBN: 978-3-030-16691-5
ISBN: 978-3-030-16692-2