---
_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. Dynamic Games and Applications. 2023;13:231-264.
doi:10.1007/s13235-022-00425-3
apa: Graham, T., Kleshnina, M., & Filar, J. A. (2023). Where do mistakes lead?
A survey of games with incompetent players. Dynamic Games and Applications.
Springer Nature. https://doi.org/10.1007/s13235-022-00425-3
chicago: Graham, Thomas, Maria Kleshnina, and Jerzy A. Filar. “Where Do Mistakes
Lead? A Survey of Games with Incompetent Players.” Dynamic Games and Applications.
Springer Nature, 2023. https://doi.org/10.1007/s13235-022-00425-3.
ieee: T. Graham, M. Kleshnina, and J. A. Filar, “Where do mistakes lead? A survey
of games with incompetent players,” Dynamic Games and Applications, 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.” Dynamic Games and Applications, vol. 13, Springer Nature, 2023,
pp. 231–64, doi:10.1007/s13235-022-00425-3.
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:
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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
relation: main_file
success: 1
file_date_updated: 2022-02-21T08:54:17Z
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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: '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. PLoS One. 2023;18(2):e0279838. doi:10.1371/journal.pone.0279838
apa: Mckerral, J. C., Kleshnina, M., Ejov, V., Bartle, L., Mitchell, J. G., &
Filar, J. A. (2023). Empirical parameterisation and dynamical analysis of the
allometric Rosenzweig-MacArthur equations. PLoS One. Public Library of
Science. https://doi.org/10.1371/journal.pone.0279838
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.” PLoS One. Public Library
of Science, 2023. https://doi.org/10.1371/journal.pone.0279838.
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,” PLoS One, 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.” PLoS One, vol. 18, no.
2, Public Library of Science, 2023, p. e0279838, doi:10.1371/journal.pone.0279838.
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
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- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: e0279838
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publication: PLoS One
publication_identifier:
eissn:
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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: '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. Nature Communications.
2023;14. doi:10.1038/s41467-023-39625-9
apa: Kleshnina, M., Hilbe, C., Simsa, S., Chatterjee, K., & Nowak, M. A. (2023).
The effect of environmental information on evolution of cooperation in stochastic
games. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-023-39625-9
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.” Nature Communications. Springer Nature,
2023. https://doi.org/10.1038/s41467-023-39625-9.
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,”
Nature Communications, 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.” Nature Communications, vol. 14, 4153,
Springer Nature, 2023, doi:10.1038/s41467-023-39625-9.
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: 2023-12-13T11:42:38Z
day: '12'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1038/s41467-023-39625-9
ec_funded: 1
external_id:
isi:
- '001029450400031'
pmid:
- '37438341'
file:
- access_level: open_access
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
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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:10.5281/ZENODO.8059564'
apa: 'Kleshnina, M. (2023). kleshnina/stochgames_info: The effect of environmental
information on evolution of cooperation in stochastic games. Zenodo. https://doi.org/10.5281/ZENODO.8059564'
chicago: 'Kleshnina, Maria. “Kleshnina/Stochgames_info: The Effect of Environmental
Information on Evolution of Cooperation in Stochastic Games.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.8059564.'
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, 10.5281/ZENODO.8059564.'
mla: 'Kleshnina, Maria. Kleshnina/Stochgames_info: The Effect of Environmental
Information on Evolution of Cooperation in Stochastic Games. Zenodo, 2023,
doi:10.5281/ZENODO.8059564.'
short: M. Kleshnina, (2023).
date_created: 2023-07-31T11:30:46Z
date_published: 2023-06-20T00:00:00Z
date_updated: 2023-12-13T11:42:37Z
day: '20'
ddc:
- '000'
department:
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doi: 10.5281/ZENODO.8059564
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url: https://doi.org/10.5281/zenodo.8059564
month: '06'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
record:
- 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: '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. PLoS Computational Biology. 2021;17(4).
doi:10.1371/journal.pcbi.1008523
apa: Kleshnina, M., Streipert, S. S., Filar, J. A., & Chatterjee, K. (2021).
Mistakes can stabilise the dynamics of rock-paper-scissors games. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1008523
chicago: Kleshnina, Maria, Sabrina S. Streipert, Jerzy A. Filar, and Krishnendu
Chatterjee. “Mistakes Can Stabilise the Dynamics of Rock-Paper-Scissors Games.”
PLoS Computational Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008523.
ieee: M. Kleshnina, S. S. Streipert, J. A. Filar, and K. Chatterjee, “Mistakes can
stabilise the dynamics of rock-paper-scissors games,” PLoS Computational Biology,
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.” PLoS Computational Biology, vol. 17, no. 4, e1008523, Public Library
of Science, 2021, doi:10.1371/journal.pcbi.1008523.
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: 2023-08-08T13:31:08Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1008523
ec_funded: 1
external_id:
isi:
- '000639711200001'
file:
- access_level: open_access
checksum: a94ebe0c4116f5047eaa6029e54d2dac
content_type: application/pdf
creator: kschuh
date_created: 2021-05-11T13:50:06Z
date_updated: 2021-05-11T13:50:06Z
file_id: '9385'
file_name: 2021_pcbi_Kleshnina.pdf
file_size: 1323820
relation: main_file
success: 1
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'
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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. Mathematics. 2020;8(11). doi:10.3390/math8111945
apa: Kleshnina, M., Streipert, S., Filar, J., & Chatterjee, K. (2020). Prioritised
learning in snowdrift-type games. Mathematics. MDPI. https://doi.org/10.3390/math8111945
chicago: Kleshnina, Maria, Sabrina Streipert, Jerzy Filar, and Krishnendu Chatterjee.
“Prioritised Learning in Snowdrift-Type Games.” Mathematics. MDPI, 2020.
https://doi.org/10.3390/math8111945.
ieee: M. Kleshnina, S. Streipert, J. Filar, and K. Chatterjee, “Prioritised learning
in snowdrift-type games,” Mathematics, 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.” Mathematics,
vol. 8, no. 11, 1945, MDPI, 2020, doi:10.3390/math8111945.
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: 2023-08-22T13:25:45Z
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title: Prioritised learning in snowdrift-type games
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