Finite population trust game replicators

Garrison Greenwood; Hussein Abbass; Eleni Petraki

doi:10.1007/978-3-319-28270-1_27

Finite population trust game replicators

Garrison Greenwood, Hussein Abbass, Eleni Petraki

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

Our previous work introduced the N player trust game and examined the dynamics of this game using replicator dynamics for an infinite population. In finite populations, quantization becomes a necessity that introduces discontinuity in the trajectory space, which can impact the dynamics of the game differently. In this paper, we present an analysis of replicator dynamics of the N player trust game in finite populations. The analysis reveals that, quantization indeed introduces fixed points in the interior of the 2-simplex that were not present in the infinite population analysis. However, there is no guarantee that these fixed points will continue to exist for any arbitrary population size; thus, they are clearly an artifact of quantization. In general, the evolutionary dynamics of the finite population are qualitatively similar to the infinite population. This suggests that for the proposed trust game, trusters will be extinct if the population contains an untrustworthy player. Therefore, trusting is an evolutionary unstable strategy.

Original language	English
Title of host publication	Artificial Life and Computational Intelligence
Subtitle of host publication	Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings
Editors	Tapabrata Ray, Ruhul Sarker, Xiaodong Li
Place of Publication	Cham, Switzerland
Publisher	Springer
Pages	324-335
Number of pages	12
Volume	9592
ISBN (Electronic)	9783319282701
ISBN (Print)	9783319282695
DOIs	https://doi.org/10.1007/978-3-319-28270-1_27
Publication status	Published - 2016
Event	2nd Australasian Conference on Artificial Life and Computational Intelligence - Canberra, Australia Duration: 2 Feb 2016 → 5 Feb 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9592
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd Australasian Conference on Artificial Life and Computational Intelligence
Abbreviated title	ACALCI 2016
Country/Territory	Australia
City	Canberra
Period	2/02/16 → 5/02/16

Access to Document

10.1007/978-3-319-28270-1_27

Cite this

Greenwood, G., Abbass, H., & Petraki, E. (2016). Finite population trust game replicators. In T. Ray, R. Sarker, & X. Li (Eds.), Artificial Life and Computational Intelligence: Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings (Vol. 9592, pp. 324-335). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9592). Springer. https://doi.org/10.1007/978-3-319-28270-1_27

Greenwood, Garrison ; Abbass, Hussein ; Petraki, Eleni. / Finite population trust game replicators. Artificial Life and Computational Intelligence: Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings. editor / Tapabrata Ray ; Ruhul Sarker ; Xiaodong Li. Vol. 9592 Cham, Switzerland : Springer, 2016. pp. 324-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Our previous work introduced the N player trust game and examined the dynamics of this game using replicator dynamics for an infinite population. In finite populations, quantization becomes a necessity that introduces discontinuity in the trajectory space, which can impact the dynamics of the game differently. In this paper, we present an analysis of replicator dynamics of the N player trust game in finite populations. The analysis reveals that, quantization indeed introduces fixed points in the interior of the 2-simplex that were not present in the infinite population analysis. However, there is no guarantee that these fixed points will continue to exist for any arbitrary population size; thus, they are clearly an artifact of quantization. In general, the evolutionary dynamics of the finite population are qualitatively similar to the infinite population. This suggests that for the proposed trust game, trusters will be extinct if the population contains an untrustworthy player. Therefore, trusting is an evolutionary unstable strategy.",

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Greenwood, G, Abbass, H & Petraki, E 2016, Finite population trust game replicators. in T Ray, R Sarker & X Li (eds), Artificial Life and Computational Intelligence: Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings. vol. 9592, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9592, Springer, Cham, Switzerland, pp. 324-335, 2nd Australasian Conference on Artificial Life and Computational Intelligence, Canberra, Australia, 2/02/16. https://doi.org/10.1007/978-3-319-28270-1_27

Finite population trust game replicators. / Greenwood, Garrison; Abbass, Hussein; Petraki, Eleni.
Artificial Life and Computational Intelligence: Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings. ed. / Tapabrata Ray; Ruhul Sarker; Xiaodong Li. Vol. 9592 Cham, Switzerland: Springer, 2016. p. 324-335 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9592).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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PY - 2016

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N2 - Our previous work introduced the N player trust game and examined the dynamics of this game using replicator dynamics for an infinite population. In finite populations, quantization becomes a necessity that introduces discontinuity in the trajectory space, which can impact the dynamics of the game differently. In this paper, we present an analysis of replicator dynamics of the N player trust game in finite populations. The analysis reveals that, quantization indeed introduces fixed points in the interior of the 2-simplex that were not present in the infinite population analysis. However, there is no guarantee that these fixed points will continue to exist for any arbitrary population size; thus, they are clearly an artifact of quantization. In general, the evolutionary dynamics of the finite population are qualitatively similar to the infinite population. This suggests that for the proposed trust game, trusters will be extinct if the population contains an untrustworthy player. Therefore, trusting is an evolutionary unstable strategy.

AB - Our previous work introduced the N player trust game and examined the dynamics of this game using replicator dynamics for an infinite population. In finite populations, quantization becomes a necessity that introduces discontinuity in the trajectory space, which can impact the dynamics of the game differently. In this paper, we present an analysis of replicator dynamics of the N player trust game in finite populations. The analysis reveals that, quantization indeed introduces fixed points in the interior of the 2-simplex that were not present in the infinite population analysis. However, there is no guarantee that these fixed points will continue to exist for any arbitrary population size; thus, they are clearly an artifact of quantization. In general, the evolutionary dynamics of the finite population are qualitatively similar to the infinite population. This suggests that for the proposed trust game, trusters will be extinct if the population contains an untrustworthy player. Therefore, trusting is an evolutionary unstable strategy.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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T2 - 2nd Australasian Conference on Artificial Life and Computational Intelligence

Y2 - 2 February 2016 through 5 February 2016

ER -

Greenwood G, Abbass H, Petraki E. Finite population trust game replicators. In Ray T, Sarker R, Li X, editors, Artificial Life and Computational Intelligence: Second Australasian Conference, ACALCI 2016 Canberra, ACT, Australia, February 2–5, 2016 Proceedings. Vol. 9592. Cham, Switzerland: Springer. 2016. p. 324-335. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-28270-1_27

Finite population trust game replicators

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