The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Evolution of extortion in Iterated Prisoner’s Dilemma games
Abstract
Iterated games are a fundamental component of economic and evolutionary game theory. They describe situations where two players interact repeatedly and have the ability to use conditional strategies that depend on the outcome of previous interactions, thus allowing for reciprocation. Recently, a new class of strategies has been proposed, so-called “zero-determinant” strategies. These strategies enforce a fixed linear relationship between one’s own payoff and that of the other player. A subset of those strategies allows “extortioners” to ensure that any increase in one player’s own payoff exceeds that of the other player by a fixed percentage. Here, we analyze the evolutionary performance of this new class of strategies. We show that in reasonably large populations, they can act as catalysts for the evolution of cooperation, similar to tit-for-tat, but that they are not the stable outcome of natural selection. In very small populations, however, extortioners hold their ground. Extortion strategies do particularly well in coevolutionary arms races between two distinct populations. Significantly, they benefit the population that evolves at the slower rate, an example of the so-called “Red King” effect. This may affect the evolution of interactions between host species and their endosymbionts.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Evolutionary game theory shows that cooperative equilibria can be achieved due to the crucial role of players signalling their trustworthiness and reliability by choosing the cooperative strategy and bearing the cost for it in the presence of non-cooperative choices by other players.
“The evolutionary game theory literature also shows that cooperative equilibria can be achieved due to the crucial role of players signalling their trustworthiness and reliability by choosing the cooperative strat egy and bearing the cost for it in the presence of non-cooperative choices by other players (Hilbe et al., 2013; Stewart and Plotkin, 2013).”
From Win Together or Lose Alone: Circular Economy and Hybrid Governance for Natural Resource Commons (2024) · cites this paper as Hilbe et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Evolutionary Dynamics: Exploring the Equations of Life
NOWAK, M. A. (2006) · doi:10.2307/j.ctvjghw98 · Cited by 2,438
Self-citationSigmund, K. (2010) · doi:10.1515/9781400832255 · Cited by 570
Self-citation
Flagged first, then by citations
Research works printed but not linked: 28
- 10.3998/mpub.20269 · DOI
- 10.1086/406755 · DOI · Paper page
- R Aumann, Survey of repeated games. Essays in Game Theory and Mathematical Economics in Honor of Oskar Morgenstern (Wissenschaftsverlag, Mannheim, Germany, 1981).
- R Axelrod The Evolution of Cooperation (Basic Books, New York, 1984).
- 10.2307/1911307 · DOI · Paper page
- D Fudenberg, E Maskin, Evolution and cooperation in noisy repeated games. Am Econ Rev 80, 274–279 (1990).
- 10.1038/364056a0 · DOI · Paper page
- 10.1142/6461 · DOI
- R Trivers, Reciprocal altruism: 30 years later. Cooperation in Primates and Humans: Mechanisms and Evolution, eds PM Kappeller, CP van Schaik (Springer, Berlin, 2006).
- 10.1073/pnas.1206569109 · DOI
- 10.1073/pnas.1208087109 · DOI
- C Adami A Hintze Winning isn’t everything: Evolutionary stability of Zero Determinant strategies. Available at http://arxiv.org/abs/1208.2666. Accessed October 12 2012. (2012). · arXiv
- 10.1080/00029890.1997.11990641 · DOI
- 10.1073/pnas.0134966100 · DOI · Paper page
- 10.1007/BF00049570 · DOI
- 10.1016/0025-5564(78)90077-9 · DOI
- J Hofbauer, Deterministic evolutionary game dynamics. Evolutionary Game Dynamics, ed K Sigmund (American Mathematical Society, Providence, RI), pp. 61–79 (2011). · DOI
- 10.1038/nature02414 · DOI
- 10.1103/PhysRevE.74.011909 · DOI
- 10.1098/rspb.2009.1171 · DOI
- 10.1016/j.jet.2005.04.006 · DOI · Paper page
- 10.1016/j.jtbi.2010.06.010 · DOI · Paper page
- 10.1038/srep00458 · DOI
- 10.1111/j.1558-5646.2011.01299.x · DOI
- 10.1006/jtbi.1994.1101 · DOI
- 10.1098/rspb.1994.0096 · DOI
- 10.1073/pnas.95.15.8676 · DOI
- 10.1103/PhysRevE.69.051913 · DOI
Cited by
Sorted by citations
Evolution of cooperation in stochastic games
Hilbe, C., Šimsa, Š., Chatterjee, K., & Nowak, M. A. (2018) · Nature · doi:10.1038/s41586-018-0277-x · Cited by 277
Self-citationA unified framework of direct and indirect reciprocity
Schmid, L., Chatterjee, K., Hilbe, C., & Nowak, M. A. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01114-8 · Cited by 161
Self-citationSmall Groups and Long Memories Promote Cooperation
Stewart, A. J., & Plotkin, J. B. (2016) · Scientific Reports · doi:10.1038/srep26889 · Cited by 78
Humans choose representatives who enforce cooperation in social dilemmas through extortion
Milinski, M., Hilbe, C., Semmann, D., Sommerfeld, R., & Marotzke, J. (2016) · Nature Communications · doi:10.1038/ncomms10915 · Cited by 62
Self-citationWin Together or Lose Alone: Circular Economy and Hybrid Governance for Natural Resource Commons
Becchetti, L., Bova, D. M., & Raffaele, L. (2024) · doi:10.2139/ssrn.4880178 · Cited by 16
Stochastic evolutionary dynamics of trust games with asymmetric parameters
Lim, I. S. (2020) · Physical review. E · doi:10.1103/physreve.102.062419 · Cited by 12
Metadata
- Authors
- Hilbe, C., Nowak, M. A., & Sigmund, K.
- Affiliations
- Evolutionary Theory Group, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany;
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138;
- Faculty of Mathematics, University of Vienna, A-1090 Vienna, Austria; and
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-04-09
- Volume
- 110
- Issue
- 17
- Pages
- 6913-6918
- ISSN
- 0027-8424
- 1091-6490
- Cited by
- 275
- References
- 2
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review