---
_id: '10770'
abstract:
- lang: eng
  text: Mathematical models often aim to describe a complicated mechanism in a cohesive
    and simple manner. However, reaching perfect balance between being simple enough
    or overly simplistic is a challenging task. Frequently, game-theoretic models
    have an underlying assumption that players, whenever they choose to execute a
    specific action, do so perfectly. In fact, it is rare that action execution perfectly
    coincides with intentions of individuals, giving rise to behavioural mistakes.
    The concept of incompetence of players was suggested to address this issue in
    game-theoretic settings. Under the assumption of incompetence, players have non-zero
    probabilities of executing a different strategy from the one they chose, leading
    to stochastic outcomes of the interactions. In this article, we survey results
    related to the concept of incompetence in classic as well as evolutionary game
    theory and provide several new results. We also suggest future extensions of the
    model and argue why it is important to take into account behavioural mistakes
    when analysing interactions among players in both economic and biological settings.
acknowledgement: "The authors would like to acknowledge stimulating email discussions
  with Dr Wayne Lobb of W.A. Lobb LLC on the topic of evolutionary games. We also
  thank Dr Thomas Taimre for his input to the material in Sect. 3.\r\nThe authors
  would like to acknowledge partial support from the Australian Research Council under
  the Discovery grant DP180101602 and support by the European Union’s Horizon 2020
  research and innovation program under the Marie Sklodowska-Curie Grant Agreement
  #754411."
article_processing_charge: No
article_type: original
author:
- first_name: Thomas
  full_name: Graham, Thomas
  last_name: Graham
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
- first_name: Jerzy A.
  full_name: Filar, Jerzy A.
  last_name: Filar
citation:
  ama: Graham T, Kleshnina M, Filar JA. Where do mistakes lead? A survey of games
    with incompetent players. <i>Dynamic Games and Applications</i>. 2023;13:231-264.
    doi:<a href="https://doi.org/10.1007/s13235-022-00425-3">10.1007/s13235-022-00425-3</a>
  apa: Graham, T., Kleshnina, M., &#38; Filar, J. A. (2023). Where do mistakes lead?
    A survey of games with incompetent players. <i>Dynamic Games and Applications</i>.
    Springer Nature. <a href="https://doi.org/10.1007/s13235-022-00425-3">https://doi.org/10.1007/s13235-022-00425-3</a>
  chicago: Graham, Thomas, Maria Kleshnina, and Jerzy A. Filar. “Where Do Mistakes
    Lead? A Survey of Games with Incompetent Players.” <i>Dynamic Games and Applications</i>.
    Springer Nature, 2023. <a href="https://doi.org/10.1007/s13235-022-00425-3">https://doi.org/10.1007/s13235-022-00425-3</a>.
  ieee: T. Graham, M. Kleshnina, and J. A. Filar, “Where do mistakes lead? A survey
    of games with incompetent players,” <i>Dynamic Games and Applications</i>, vol.
    13. Springer Nature, pp. 231–264, 2023.
  ista: Graham T, Kleshnina M, Filar JA. 2023. Where do mistakes lead? A survey of
    games with incompetent players. Dynamic Games and Applications. 13, 231–264.
  mla: Graham, Thomas, et al. “Where Do Mistakes Lead? A Survey of Games with Incompetent
    Players.” <i>Dynamic Games and Applications</i>, vol. 13, Springer Nature, 2023,
    pp. 231–64, doi:<a href="https://doi.org/10.1007/s13235-022-00425-3">10.1007/s13235-022-00425-3</a>.
  short: T. Graham, M. Kleshnina, J.A. Filar, Dynamic Games and Applications 13 (2023)
    231–264.
date_created: 2022-02-20T23:01:32Z
date_published: 2023-03-01T00:00:00Z
date_updated: 2023-10-04T09:24:30Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/s13235-022-00425-3
ec_funded: 1
external_id:
  isi:
  - '000753777100001'
file:
- access_level: open_access
  checksum: cd53b07e96f9030ddb348f305e5b58c7
  content_type: application/pdf
  creator: dernst
  date_created: 2022-02-21T08:54:17Z
  date_updated: 2022-02-21T08:54:17Z
  file_id: '10781'
  file_name: 2022_DynamicGamesApplic_Graham.pdf
  file_size: 1890512
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file_date_updated: 2022-02-21T08:54:17Z
has_accepted_license: '1'
intvolume: '        13'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 231-264
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: Dynamic Games and Applications
publication_identifier:
  eissn:
  - 2153-0793
  issn:
  - 2153-0785
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Where do mistakes lead? A survey of games with incompetent players
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2023'
...
---
_id: '13258'
abstract:
- lang: eng
  text: Many human interactions feature the characteristics of social dilemmas where
    individual actions have consequences for the group and the environment. The feedback
    between behavior and environment can be studied with the framework of stochastic
    games. In stochastic games, the state of the environment can change, depending
    on the choices made by group members. Past work suggests that such feedback can
    reinforce cooperative behaviors. In particular, cooperation can evolve in stochastic
    games even if it is infeasible in each separate repeated game. In stochastic games,
    participants have an interest in conditioning their strategies on the state of
    the environment. Yet in many applications, precise information about the state
    could be scarce. Here, we study how the availability of information (or lack thereof)
    shapes evolution of cooperation. Already for simple examples of two state games
    we find surprising effects. In some cases, cooperation is only possible if there
    is precise information about the state of the environment. In other cases, cooperation
    is most abundant when there is no information about the state of the environment.
    We systematically analyze all stochastic games of a given complexity class, to
    determine when receiving information about the environment is better, neutral,
    or worse for evolution of cooperation.
acknowledgement: 'This work was supported by the European Research Council CoG 863818
  (ForM-SMArt) (to K.C.), the European Research Council Starting Grant 850529: E-DIRECT
  (to C.H.), the European Union’s Horizon 2020 research and innovation program under
  the Marie Sklodowska-Curie Grant Agreement #754411 and the French Agence Nationale
  de la Recherche (under the Investissement d’Avenir programme, ANR-17-EURE-0010)
  (to M.K.).'
article_number: '4153'
article_processing_charge: Yes
article_type: original
author:
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
- first_name: Christian
  full_name: Hilbe, Christian
  id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87
  last_name: Hilbe
  orcid: 0000-0001-5116-955X
- first_name: Stepan
  full_name: Simsa, Stepan
  id: 409d615c-2f95-11ee-b934-90a352102c1e
  last_name: Simsa
  orcid: 0000-0001-6687-1210
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Martin A.
  full_name: Nowak, Martin A.
  last_name: Nowak
citation:
  ama: Kleshnina M, Hilbe C, Simsa S, Chatterjee K, Nowak MA. The effect of environmental
    information on evolution of cooperation in stochastic games. <i>Nature Communications</i>.
    2023;14. doi:<a href="https://doi.org/10.1038/s41467-023-39625-9">10.1038/s41467-023-39625-9</a>
  apa: Kleshnina, M., Hilbe, C., Simsa, S., Chatterjee, K., &#38; Nowak, M. A. (2023).
    The effect of environmental information on evolution of cooperation in stochastic
    games. <i>Nature Communications</i>. Springer Nature. <a href="https://doi.org/10.1038/s41467-023-39625-9">https://doi.org/10.1038/s41467-023-39625-9</a>
  chicago: Kleshnina, Maria, Christian Hilbe, Stepan Simsa, Krishnendu Chatterjee,
    and Martin A. Nowak. “The Effect of Environmental Information on Evolution of
    Cooperation in Stochastic Games.” <i>Nature Communications</i>. Springer Nature,
    2023. <a href="https://doi.org/10.1038/s41467-023-39625-9">https://doi.org/10.1038/s41467-023-39625-9</a>.
  ieee: M. Kleshnina, C. Hilbe, S. Simsa, K. Chatterjee, and M. A. Nowak, “The effect
    of environmental information on evolution of cooperation in stochastic games,”
    <i>Nature Communications</i>, vol. 14. Springer Nature, 2023.
  ista: Kleshnina M, Hilbe C, Simsa S, Chatterjee K, Nowak MA. 2023. The effect of
    environmental information on evolution of cooperation in stochastic games. Nature
    Communications. 14, 4153.
  mla: Kleshnina, Maria, et al. “The Effect of Environmental Information on Evolution
    of Cooperation in Stochastic Games.” <i>Nature Communications</i>, vol. 14, 4153,
    Springer Nature, 2023, doi:<a href="https://doi.org/10.1038/s41467-023-39625-9">10.1038/s41467-023-39625-9</a>.
  short: M. Kleshnina, C. Hilbe, S. Simsa, K. Chatterjee, M.A. Nowak, Nature Communications
    14 (2023).
date_created: 2023-07-23T22:01:11Z
date_published: 2023-07-12T00:00:00Z
date_updated: 2025-07-14T09:09:53Z
day: '12'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1038/s41467-023-39625-9
ec_funded: 1
external_id:
  isi:
  - '001029450400031'
  pmid:
  - '37438341'
file:
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  checksum: 5aceefdfe76686267b93ae4fe81899f1
  content_type: application/pdf
  creator: dernst
  date_created: 2023-07-31T11:32:36Z
  date_updated: 2023-07-31T11:32:36Z
  file_id: '13337'
  file_name: 2023_NatureComm_Kleshnina.pdf
  file_size: 1601682
  relation: main_file
  success: 1
file_date_updated: 2023-07-31T11:32:36Z
has_accepted_license: '1'
intvolume: '        14'
isi: 1
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: Nature Communications
publication_identifier:
  eissn:
  - 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  record:
  - id: '13336'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: The effect of environmental information on evolution of cooperation in stochastic
  games
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2023'
...
---
_id: '13336'
article_processing_charge: No
author:
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
citation:
  ama: 'Kleshnina M. kleshnina/stochgames_info: The effect of environmental information
    on evolution of cooperation in stochastic games. 2023. doi:<a href="https://doi.org/10.5281/ZENODO.8059564">10.5281/ZENODO.8059564</a>'
  apa: 'Kleshnina, M. (2023). kleshnina/stochgames_info: The effect of environmental
    information on evolution of cooperation in stochastic games. Zenodo. <a href="https://doi.org/10.5281/ZENODO.8059564">https://doi.org/10.5281/ZENODO.8059564</a>'
  chicago: 'Kleshnina, Maria. “Kleshnina/Stochgames_info: The Effect of Environmental
    Information on Evolution of Cooperation in Stochastic Games.” Zenodo, 2023. <a
    href="https://doi.org/10.5281/ZENODO.8059564">https://doi.org/10.5281/ZENODO.8059564</a>.'
  ieee: 'M. Kleshnina, “kleshnina/stochgames_info: The effect of environmental information
    on evolution of cooperation in stochastic games.” Zenodo, 2023.'
  ista: 'Kleshnina M. 2023. kleshnina/stochgames_info: The effect of environmental
    information on evolution of cooperation in stochastic games, Zenodo, <a href="https://doi.org/10.5281/ZENODO.8059564">10.5281/ZENODO.8059564</a>.'
  mla: 'Kleshnina, Maria. <i>Kleshnina/Stochgames_info: The Effect of Environmental
    Information on Evolution of Cooperation in Stochastic Games</i>. Zenodo, 2023,
    doi:<a href="https://doi.org/10.5281/ZENODO.8059564">10.5281/ZENODO.8059564</a>.'
  short: M. Kleshnina, (2023).
date_created: 2023-07-31T11:30:46Z
date_published: 2023-06-20T00:00:00Z
date_updated: 2025-07-14T09:09:53Z
day: '20'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.5281/ZENODO.8059564
main_file_link:
- open_access: '1'
  url: https://doi.org/10.5281/zenodo.8059564
month: '06'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
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  - id: '13258'
    relation: used_in_publication
    status: public
status: public
title: 'kleshnina/stochgames_info: The effect of environmental information on evolution
  of cooperation in stochastic games'
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12706'
abstract:
- lang: eng
  text: Allometric settings of population dynamics models are appealing due to their
    parsimonious nature and broad utility when studying system level effects. Here,
    we parameterise the size-scaled Rosenzweig-MacArthur differential equations to
    eliminate prey-mass dependency, facilitating an in depth analytic study of the
    equations which incorporates scaling parameters’ contributions to coexistence.
    We define the functional response term to match empirical findings, and examine
    situations where metabolic theory derivations and observation diverge. The dynamical
    properties of the Rosenzweig-MacArthur system, encompassing the distribution of
    size-abundance equilibria, the scaling of period and amplitude of population cycling,
    and relationships between predator and prey abundances, are consistent with empirical
    observation. Our parameterisation is an accurate minimal model across 15+ orders
    of mass magnitude.
acknowledgement: "This research was supported by an Australian Government Research
  Training Program\r\n(RTP) Scholarship to JCM (https://www.dese.gov.au), and LB is
  supported by the Centre de\r\nrecherche sur le vieillissement Fellowship Program.
  The funders had no role in study design, data collection and analysis, decision
  to publish, or preparation of the manuscript."
article_processing_charge: No
article_type: original
author:
- first_name: Jody C.
  full_name: Mckerral, Jody C.
  last_name: Mckerral
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
- first_name: Vladimir
  full_name: Ejov, Vladimir
  last_name: Ejov
- first_name: Louise
  full_name: Bartle, Louise
  last_name: Bartle
- first_name: James G.
  full_name: Mitchell, James G.
  last_name: Mitchell
- first_name: Jerzy A.
  full_name: Filar, Jerzy A.
  last_name: Filar
citation:
  ama: Mckerral JC, Kleshnina M, Ejov V, Bartle L, Mitchell JG, Filar JA. Empirical
    parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
    equations. <i>PLoS One</i>. 2023;18(2):e0279838. doi:<a href="https://doi.org/10.1371/journal.pone.0279838">10.1371/journal.pone.0279838</a>
  apa: Mckerral, J. C., Kleshnina, M., Ejov, V., Bartle, L., Mitchell, J. G., &#38;
    Filar, J. A. (2023). Empirical parameterisation and dynamical analysis of the
    allometric Rosenzweig-MacArthur equations. <i>PLoS One</i>. Public Library of
    Science. <a href="https://doi.org/10.1371/journal.pone.0279838">https://doi.org/10.1371/journal.pone.0279838</a>
  chicago: Mckerral, Jody C., Maria Kleshnina, Vladimir Ejov, Louise Bartle, James
    G. Mitchell, and Jerzy A. Filar. “Empirical Parameterisation and Dynamical Analysis
    of the Allometric Rosenzweig-MacArthur Equations.” <i>PLoS One</i>. Public Library
    of Science, 2023. <a href="https://doi.org/10.1371/journal.pone.0279838">https://doi.org/10.1371/journal.pone.0279838</a>.
  ieee: J. C. Mckerral, M. Kleshnina, V. Ejov, L. Bartle, J. G. Mitchell, and J. A.
    Filar, “Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
    equations,” <i>PLoS One</i>, vol. 18, no. 2. Public Library of Science, p. e0279838,
    2023.
  ista: Mckerral JC, Kleshnina M, Ejov V, Bartle L, Mitchell JG, Filar JA. 2023. Empirical
    parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
    equations. PLoS One. 18(2), e0279838.
  mla: Mckerral, Jody C., et al. “Empirical Parameterisation and Dynamical Analysis
    of the Allometric Rosenzweig-MacArthur Equations.” <i>PLoS One</i>, vol. 18, no.
    2, Public Library of Science, 2023, p. e0279838, doi:<a href="https://doi.org/10.1371/journal.pone.0279838">10.1371/journal.pone.0279838</a>.
  short: J.C. Mckerral, M. Kleshnina, V. Ejov, L. Bartle, J.G. Mitchell, J.A. Filar,
    PLoS One 18 (2023) e0279838.
date_created: 2023-03-05T23:01:05Z
date_published: 2023-02-27T00:00:00Z
date_updated: 2023-10-17T12:53:30Z
day: '27'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pone.0279838
external_id:
  isi:
  - '000996122900022'
  pmid:
  - '36848357'
file:
- access_level: open_access
  checksum: 798ed5739a4117b03173e5d56e0534c9
  content_type: application/pdf
  creator: cchlebak
  date_created: 2023-03-07T10:26:45Z
  date_updated: 2023-03-07T10:26:45Z
  file_id: '12712'
  file_name: 2023_PLOSOne_Mckerral.pdf
  file_size: 1257003
  relation: main_file
  success: 1
file_date_updated: 2023-03-07T10:26:45Z
has_accepted_license: '1'
intvolume: '        18'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: e0279838
pmid: 1
publication: PLoS One
publication_identifier:
  eissn:
  - 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
  equations
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 18
year: '2023'
...
---
_id: '9381'
abstract:
- lang: eng
  text: 'A game of rock-paper-scissors is an interesting example of an interaction
    where none of the pure strategies strictly dominates all others, leading to a
    cyclic pattern. In this work, we consider an unstable version of rock-paper-scissors
    dynamics and allow individuals to make behavioural mistakes during the strategy
    execution. We show that such an assumption can break a cyclic relationship leading
    to a stable equilibrium emerging with only one strategy surviving. We consider
    two cases: completely random mistakes when individuals have no bias towards any
    strategy and a general form of mistakes. Then, we determine conditions for a strategy
    to dominate all other strategies. However, given that individuals who adopt a
    dominating strategy are still prone to behavioural mistakes in the observed behaviour,
    we may still observe extinct strategies. That is, behavioural mistakes in strategy
    execution stabilise evolutionary dynamics leading to an evolutionary stable and,
    potentially, mixed co-existence equilibrium.'
acknowledgement: Authors would like to thank Christian Hilbe and Martin Nowak for
  their inspiring and very helpful feedback on the manuscript.
article_number: e1008523
article_processing_charge: No
article_type: original
author:
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
- first_name: Sabrina S.
  full_name: Streipert, Sabrina S.
  last_name: Streipert
- first_name: Jerzy A.
  full_name: Filar, Jerzy A.
  last_name: Filar
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
citation:
  ama: Kleshnina M, Streipert SS, Filar JA, Chatterjee K. Mistakes can stabilise the
    dynamics of rock-paper-scissors games. <i>PLoS Computational Biology</i>. 2021;17(4).
    doi:<a href="https://doi.org/10.1371/journal.pcbi.1008523">10.1371/journal.pcbi.1008523</a>
  apa: Kleshnina, M., Streipert, S. S., Filar, J. A., &#38; Chatterjee, K. (2021).
    Mistakes can stabilise the dynamics of rock-paper-scissors games. <i>PLoS Computational
    Biology</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1008523">https://doi.org/10.1371/journal.pcbi.1008523</a>
  chicago: Kleshnina, Maria, Sabrina S. Streipert, Jerzy A. Filar, and Krishnendu
    Chatterjee. “Mistakes Can Stabilise the Dynamics of Rock-Paper-Scissors Games.”
    <i>PLoS Computational Biology</i>. Public Library of Science, 2021. <a href="https://doi.org/10.1371/journal.pcbi.1008523">https://doi.org/10.1371/journal.pcbi.1008523</a>.
  ieee: M. Kleshnina, S. S. Streipert, J. A. Filar, and K. Chatterjee, “Mistakes can
    stabilise the dynamics of rock-paper-scissors games,” <i>PLoS Computational Biology</i>,
    vol. 17, no. 4. Public Library of Science, 2021.
  ista: Kleshnina M, Streipert SS, Filar JA, Chatterjee K. 2021. Mistakes can stabilise
    the dynamics of rock-paper-scissors games. PLoS Computational Biology. 17(4),
    e1008523.
  mla: Kleshnina, Maria, et al. “Mistakes Can Stabilise the Dynamics of Rock-Paper-Scissors
    Games.” <i>PLoS Computational Biology</i>, vol. 17, no. 4, e1008523, Public Library
    of Science, 2021, doi:<a href="https://doi.org/10.1371/journal.pcbi.1008523">10.1371/journal.pcbi.1008523</a>.
  short: M. Kleshnina, S.S. Streipert, J.A. Filar, K. Chatterjee, PLoS Computational
    Biology 17 (2021).
date_created: 2021-05-09T22:01:38Z
date_published: 2021-04-01T00:00:00Z
date_updated: 2025-07-14T09:10:04Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1008523
ec_funded: 1
external_id:
  isi:
  - '000639711200001'
file:
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  date_created: 2021-05-11T13:50:06Z
  date_updated: 2021-05-11T13:50:06Z
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  file_name: 2021_pcbi_Kleshnina.pdf
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file_date_updated: 2021-05-11T13:50:06Z
has_accepted_license: '1'
intvolume: '        17'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: PLoS Computational Biology
publication_identifier:
  eissn:
  - '15537358'
  issn:
  - 1553734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Mistakes can stabilise the dynamics of rock-paper-scissors games
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 17
year: '2021'
...
---
_id: '8789'
abstract:
- lang: eng
  text: Cooperation is a ubiquitous and beneficial behavioural trait despite being
    prone to exploitation by free-riders. Hence, cooperative populations are prone
    to invasions by selfish individuals. However, a population consisting of only
    free-riders typically does not survive. Thus, cooperators and free-riders often
    coexist in some proportion. An evolutionary version of a Snowdrift Game proved
    its efficiency in analysing this phenomenon. However, what if the system has already
    reached its stable state but was perturbed due to a change in environmental conditions?
    Then, individuals may have to re-learn their effective strategies. To address
    this, we consider behavioural mistakes in strategic choice execution, which we
    refer to as incompetence. Parametrising the propensity to make such mistakes allows
    for a mathematical description of learning. We compare strategies based on their
    relative strategic advantage relying on both fitness and learning factors. When
    strategies are learned at distinct rates, allowing learning according to a prescribed
    order is optimal. Interestingly, the strategy with the lowest strategic advantage
    should be learnt first if we are to optimise fitness over the learning path. Then,
    the differences between strategies are balanced out in order to minimise the effect
    of behavioural uncertainty.
acknowledgement: "This work was supported by the European Union’s Horizon 2020 research
  and innovation program under the Marie Sklodowska-Curie Grant Agreement #754411,
  the Australian Research Council Discovery Grants DP160101236 and DP150100618, and
  the European Research Council Consolidator Grant 863818 (FoRM-SMArt).\r\nAuthors
  would like to thank Patrick McKinlay for his work on the preliminary results for
  this paper."
article_number: '1945'
article_processing_charge: No
article_type: original
author:
- first_name: Maria
  full_name: Kleshnina, Maria
  id: 4E21749C-F248-11E8-B48F-1D18A9856A87
  last_name: Kleshnina
- first_name: Sabrina
  full_name: Streipert, Sabrina
  last_name: Streipert
- first_name: Jerzy
  full_name: Filar, Jerzy
  last_name: Filar
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
citation:
  ama: Kleshnina M, Streipert S, Filar J, Chatterjee K. Prioritised learning in snowdrift-type
    games. <i>Mathematics</i>. 2020;8(11). doi:<a href="https://doi.org/10.3390/math8111945">10.3390/math8111945</a>
  apa: Kleshnina, M., Streipert, S., Filar, J., &#38; Chatterjee, K. (2020). Prioritised
    learning in snowdrift-type games. <i>Mathematics</i>. MDPI. <a href="https://doi.org/10.3390/math8111945">https://doi.org/10.3390/math8111945</a>
  chicago: Kleshnina, Maria, Sabrina Streipert, Jerzy Filar, and Krishnendu Chatterjee.
    “Prioritised Learning in Snowdrift-Type Games.” <i>Mathematics</i>. MDPI, 2020.
    <a href="https://doi.org/10.3390/math8111945">https://doi.org/10.3390/math8111945</a>.
  ieee: M. Kleshnina, S. Streipert, J. Filar, and K. Chatterjee, “Prioritised learning
    in snowdrift-type games,” <i>Mathematics</i>, vol. 8, no. 11. MDPI, 2020.
  ista: Kleshnina M, Streipert S, Filar J, Chatterjee K. 2020. Prioritised learning
    in snowdrift-type games. Mathematics. 8(11), 1945.
  mla: Kleshnina, Maria, et al. “Prioritised Learning in Snowdrift-Type Games.” <i>Mathematics</i>,
    vol. 8, no. 11, 1945, MDPI, 2020, doi:<a href="https://doi.org/10.3390/math8111945">10.3390/math8111945</a>.
  short: M. Kleshnina, S. Streipert, J. Filar, K. Chatterjee, Mathematics 8 (2020).
date_created: 2020-11-22T23:01:24Z
date_published: 2020-11-04T00:00:00Z
date_updated: 2025-07-14T09:09:49Z
day: '04'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.3390/math8111945
ec_funded: 1
external_id:
  isi:
  - '000593962100001'
file:
- access_level: open_access
  checksum: 61cfcc3b35760656ce7a9385a4ace5d2
  content_type: application/pdf
  creator: dernst
  date_created: 2020-11-23T13:06:30Z
  date_updated: 2020-11-23T13:06:30Z
  file_id: '8797'
  file_name: 2020_Mathematics_Kleshnina.pdf
  file_size: 565191
  relation: main_file
  success: 1
file_date_updated: 2020-11-23T13:06:30Z
has_accepted_license: '1'
intvolume: '         8'
isi: 1
issue: '11'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Mathematics
publication_identifier:
  eissn:
  - '22277390'
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Prioritised learning in snowdrift-type games
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 8
year: '2020'
...