---
_id: '14259'
abstract:
- lang: eng
text: "We provide a learning-based technique for guessing a winning strategy in
a parity game originating from an LTL synthesis problem. A cheaply obtained guess
can be useful in several applications. Not only can the guessed strategy be applied
as best-effort in cases where the game’s huge size prohibits rigorous approaches,
but it can also increase the scalability of rigorous LTL synthesis in several
ways. Firstly, checking whether a guessed strategy is winning is easier than constructing
one. Secondly, even if the guess is wrong in some places, it can be fixed by strategy
iteration faster than constructing one from scratch. Thirdly, the guess can be
used in on-the-fly approaches to prioritize exploration in the most fruitful directions.\r\nIn
contrast to previous works, we (i) reflect the highly structured logical information
in game’s states, the so-called semantic labelling, coming from the recent LTL-to-automata
translations, and (ii) learn to reflect it properly by learning from previously
solved games, bringing the solving process closer to human-like reasoning."
acknowledgement: This research was funded in part by the German Research Foundation
(DFG) project 427755713 Group-By Objectives in Probabilistic Verification (GOPro).
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Jan
full_name: Kretinsky, Jan
id: 44CEF464-F248-11E8-B48F-1D18A9856A87
last_name: Kretinsky
orcid: 0000-0002-8122-2881
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Maximilian
full_name: Prokop, Maximilian
last_name: Prokop
- first_name: Sabine
full_name: Rieder, Sabine
last_name: Rieder
citation:
ama: 'Kretinsky J, Meggendorfer T, Prokop M, Rieder S. Guessing winning policies
in LTL synthesis by semantic learning. In: 35th International Conference on
Computer Aided Verification . Vol 13964. Springer Nature; 2023:390-414. doi:10.1007/978-3-031-37706-8_20'
apa: 'Kretinsky, J., Meggendorfer, T., Prokop, M., & Rieder, S. (2023). Guessing
winning policies in LTL synthesis by semantic learning. In 35th International
Conference on Computer Aided Verification (Vol. 13964, pp. 390–414). Paris,
France: Springer Nature. https://doi.org/10.1007/978-3-031-37706-8_20'
chicago: Kretinsky, Jan, Tobias Meggendorfer, Maximilian Prokop, and Sabine Rieder.
“Guessing Winning Policies in LTL Synthesis by Semantic Learning.” In 35th
International Conference on Computer Aided Verification , 13964:390–414. Springer
Nature, 2023. https://doi.org/10.1007/978-3-031-37706-8_20.
ieee: J. Kretinsky, T. Meggendorfer, M. Prokop, and S. Rieder, “Guessing winning
policies in LTL synthesis by semantic learning,” in 35th International Conference
on Computer Aided Verification , Paris, France, 2023, vol. 13964, pp. 390–414.
ista: 'Kretinsky J, Meggendorfer T, Prokop M, Rieder S. 2023. Guessing winning policies
in LTL synthesis by semantic learning. 35th International Conference on Computer
Aided Verification . CAV: Computer Aided Verification, LNCS, vol. 13964, 390–414.'
mla: Kretinsky, Jan, et al. “Guessing Winning Policies in LTL Synthesis by Semantic
Learning.” 35th International Conference on Computer Aided Verification ,
vol. 13964, Springer Nature, 2023, pp. 390–414, doi:10.1007/978-3-031-37706-8_20.
short: J. Kretinsky, T. Meggendorfer, M. Prokop, S. Rieder, in:, 35th International
Conference on Computer Aided Verification , Springer Nature, 2023, pp. 390–414.
conference:
end_date: 2023-07-22
location: Paris, France
name: 'CAV: Computer Aided Verification'
start_date: 2023-07-17
date_created: 2023-09-03T22:01:16Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2023-09-06T08:27:33Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37706-8_20
file:
- access_level: open_access
checksum: ed66278b61bb869e1baba3d9b9081271
content_type: application/pdf
creator: dernst
date_created: 2023-09-06T08:25:50Z
date_updated: 2023-09-06T08:25:50Z
file_id: '14276'
file_name: 2023_LNCS_CAV_Kretinsky.pdf
file_size: 428354
relation: main_file
success: 1
file_date_updated: 2023-09-06T08:25:50Z
has_accepted_license: '1'
intvolume: ' 13964'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '07'
oa: 1
oa_version: Published Version
page: 390-414
publication: '35th International Conference on Computer Aided Verification '
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377051'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Guessing winning policies in LTL synthesis by semantic learning
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13964
year: '2023'
...
---
_id: '14318'
abstract:
- lang: eng
text: "Probabilistic recurrence relations (PRRs) are a standard formalism for describing
the runtime of a randomized algorithm. Given a PRR and a time limit κ, we consider
the tail probability Pr[T≥κ], i.e., the probability that the randomized runtime
T of the PRR exceeds κ. Our focus is the formal analysis of tail bounds that aims
at finding a tight asymptotic upper bound u≥Pr[T≥κ]. To address this problem,
the classical and most well-known approach is the cookbook method by Karp (JACM
1994), while other approaches are mostly limited to deriving tail bounds of specific
PRRs via involved custom analysis.\r\nIn this work, we propose a novel approach
for deriving the common exponentially-decreasing tail bounds for PRRs whose preprocessing
time and random passed sizes observe discrete or (piecewise) uniform distribution
and whose recursive call is either a single procedure call or a divide-and-conquer.
We first establish a theoretical approach via Markov’s inequality, and then instantiate
the theoretical approach with a template-based algorithmic approach via a refined
treatment of exponentiation. Experimental evaluation shows that our algorithmic
approach is capable of deriving tail bounds that are (i) asymptotically tighter
than Karp’s method, (ii) match the best-known manually-derived asymptotic tail
bound for QuickSelect, and (iii) is only slightly worse (with a loglogn factor)
than the manually-proven optimal asymptotic tail bound for QuickSort. Moreover,
our algorithmic approach handles all examples (including realistic PRRs such as
QuickSort, QuickSelect, DiameterComputation, etc.) in less than 0.1 s, showing
that our approach is efficient in practice."
acknowledgement: We thank Prof. Bican Xia for valuable information on the exponential
theory of reals. The work is partially supported by the National Natural Science
Foundation of China (NSFC) with Grant No. 62172271, ERC CoG 863818 (ForM-SMArt),
the Hong Kong Research Grants Council ECS Project Number 26208122, the HKUST-Kaisa
Joint Research Institute Project Grant HKJRI3A-055 and the HKUST Startup Grant R9272.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Yican
full_name: Sun, Yican
last_name: Sun
- first_name: Hongfei
full_name: Fu, Hongfei
last_name: Fu
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Amir Kafshdar
full_name: Goharshady, Amir Kafshdar
id: 391365CE-F248-11E8-B48F-1D18A9856A87
last_name: Goharshady
orcid: 0000-0003-1702-6584
citation:
ama: 'Sun Y, Fu H, Chatterjee K, Goharshady AK. Automated tail bound analysis for probabilistic
recurrence relations. In: Computer Aided Verification. Vol 13966. Springer
Nature; 2023:16-39. doi:10.1007/978-3-031-37709-9_2'
apa: 'Sun, Y., Fu, H., Chatterjee, K., & Goharshady, A. K. (2023). Automated
tail bound analysis for probabilistic recurrence relations. In Computer Aided
Verification (Vol. 13966, pp. 16–39). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_2'
chicago: Sun, Yican, Hongfei Fu, Krishnendu Chatterjee, and Amir Kafshdar Goharshady.
“Automated Tail Bound Analysis for Probabilistic Recurrence Relations.” In Computer
Aided Verification, 13966:16–39. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_2.
ieee: Y. Sun, H. Fu, K. Chatterjee, and A. K. Goharshady, “Automated tail bound
analysis for probabilistic recurrence relations,” in Computer Aided Verification,
Paris, France, 2023, vol. 13966, pp. 16–39.
ista: 'Sun Y, Fu H, Chatterjee K, Goharshady AK. 2023. Automated tail bound analysis
for probabilistic recurrence relations. Computer Aided Verification. CAV: Computer
Aided Verification, LNCS, vol. 13966, 16–39.'
mla: Sun, Yican, et al. “Automated Tail Bound Analysis for Probabilistic Recurrence
Relations.” Computer Aided Verification, vol. 13966, Springer Nature, 2023,
pp. 16–39, doi:10.1007/978-3-031-37709-9_2.
short: Y. Sun, H. Fu, K. Chatterjee, A.K. Goharshady, in:, Computer Aided Verification,
Springer Nature, 2023, pp. 16–39.
conference:
end_date: 2023-07-22
location: Paris, France
name: 'CAV: Computer Aided Verification'
start_date: 2023-07-17
date_created: 2023-09-10T22:01:12Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2023-09-20T08:25:57Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_2
ec_funded: 1
file:
- access_level: open_access
checksum: 42917e086f8c7699f3bccf84f74fe000
content_type: application/pdf
creator: dernst
date_created: 2023-09-20T08:24:47Z
date_updated: 2023-09-20T08:24:47Z
file_id: '14348'
file_name: 2023_LNCS_Sun.pdf
file_size: 624647
relation: main_file
success: 1
file_date_updated: 2023-09-20T08:24:47Z
has_accepted_license: '1'
intvolume: ' 13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 16-39
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377082'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/boyvolcano/PRR
scopus_import: '1'
status: public
title: Automated tail bound analysis for probabilistic recurrence relations
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13966
year: '2023'
...
---
_id: '14317'
abstract:
- lang: eng
text: "Markov decision processes can be viewed as transformers of probability distributions.
While this view is useful from a practical standpoint to reason about trajectories
of distributions, basic reachability and safety problems are known to be computationally
intractable (i.e., Skolem-hard) to solve in such models. Further, we show that
even for simple examples of MDPs, strategies for safety objectives over distributions
can require infinite memory and randomization.\r\nIn light of this, we present
a novel overapproximation approach to synthesize strategies in an MDP, such that
a safety objective over the distributions is met. More precisely, we develop a
new framework for template-based synthesis of certificates as affine distributional
and inductive invariants for safety objectives in MDPs. We provide two algorithms
within this framework. One can only synthesize memoryless strategies, but has
relative completeness guarantees, while the other can synthesize general strategies.
The runtime complexity of both algorithms is in PSPACE. We implement these algorithms
and show that they can solve several non-trivial examples."
acknowledgement: This work was supported in part by the ERC CoG 863818 (FoRM-SMArt)
and the European Union’s Horizon 2020 research and innovation programme under the
Marie Skłodowska-Curie Grant Agreement No. 665385 as well as DST/CEFIPRA/INRIA project
EQuaVE and SERB Matrices grant MTR/2018/00074.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: S.
full_name: Akshay, S.
last_name: Akshay
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. MDPs as distribution transformers:
Affine invariant synthesis for safety objectives. In: International Conference
on Computer Aided Verification. Vol 13966. Springer Nature; 2023:86-112. doi:10.1007/978-3-031-37709-9_5'
apa: 'Akshay, S., Chatterjee, K., Meggendorfer, T., & Zikelic, D. (2023). MDPs
as distribution transformers: Affine invariant synthesis for safety objectives.
In International Conference on Computer Aided Verification (Vol. 13966,
pp. 86–112). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_5'
chicago: 'Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic.
“MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”
In International Conference on Computer Aided Verification, 13966:86–112.
Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_5.'
ieee: 'S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution
transformers: Affine invariant synthesis for safety objectives,” in International
Conference on Computer Aided Verification, Paris, France, 2023, vol. 13966,
pp. 86–112.'
ista: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. 2023. MDPs as distribution
transformers: Affine invariant synthesis for safety objectives. International
Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS,
vol. 13966, 86–112.'
mla: 'Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis
for Safety Objectives.” International Conference on Computer Aided Verification,
vol. 13966, Springer Nature, 2023, pp. 86–112, doi:10.1007/978-3-031-37709-9_5.'
short: S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International
Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.
conference:
end_date: 2023-07-22
location: Paris, France
name: 'CAV: Computer Aided Verification'
start_date: 2023-07-17
date_created: 2023-09-10T22:01:12Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2023-09-20T09:04:40Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_5
ec_funded: 1
file:
- access_level: open_access
checksum: f143c8eedf609f20f2aad2eeb496d53f
content_type: application/pdf
creator: dernst
date_created: 2023-09-20T08:46:43Z
date_updated: 2023-09-20T08:46:43Z
file_id: '14349'
file_name: 2023_LNCS_Akshay.pdf
file_size: 531745
relation: main_file
success: 1
file_date_updated: 2023-09-20T08:46:43Z
has_accepted_license: '1'
intvolume: ' 13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 86-112
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: International Conference on Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377082'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'MDPs as distribution transformers: Affine invariant synthesis for safety objectives'
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13966
year: '2023'
...
---
_id: '12738'
abstract:
- lang: eng
text: We study turn-based stochastic zero-sum games with lexicographic preferences
over objectives. Stochastic games are standard models in control, verification,
and synthesis of stochastic reactive systems that exhibit both randomness as well
as controllable and adversarial non-determinism. Lexicographic order allows one
to consider multiple objectives with a strict preference order. To the best of
our knowledge, stochastic games with lexicographic objectives have not been studied
before. For a mixture of reachability and safety objectives, we show that deterministic
lexicographically optimal strategies exist and memory is only required to remember
the already satisfied and violated objectives. For a constant number of objectives,
we show that the relevant decision problem is in NP∩coNP, matching the current
known bound for single objectives; and in general the decision problem is PSPACE-hard
and can be solved in NEXPTIME∩coNEXPTIME. We present an algorithm that computes
the lexicographically optimal strategies via a reduction to the computation of
optimal strategies in a sequence of single-objectives games. For omega-regular
objectives, we restrict our analysis to one-player games, also known as Markov
decision processes. We show that lexicographically optimal strategies exist and
need either randomization or finite memory. We present an algorithm that solves
the relevant decision problem in polynomial time. We have implemented our algorithms
and report experimental results on various case studies.
acknowledgement: Tobias Winkler and Joost-Pieter Katoen are supported by the DFG RTG
2236 UnRAVeL and the innovation programme under the Marie Skłodowska-Curie grant
agreement No. 101008233 (Mission). Krishnendu Chatterjee is supported by the ERC
CoG 863818 (ForM-SMArt) and the Vienna Science and Technology Fund (WWTF) Project
ICT15-003. Maximilian Weininger is supported by the DFG projects 383882557 Statistical
Unbounded Verification (SUV) and 427755713 Group-By Objectives in Probabilistic
Verification (GOPro). Stefanie Mohr is supported by the DFG RTG 2428 CONVEY. Open
Access funding enabled and organized by Projekt DEAL.
article_processing_charge: No
article_type: original
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Joost P
full_name: Katoen, Joost P
id: 4524F760-F248-11E8-B48F-1D18A9856A87
last_name: Katoen
- first_name: Stefanie
full_name: Mohr, Stefanie
last_name: Mohr
- first_name: Maximilian
full_name: Weininger, Maximilian
last_name: Weininger
- first_name: Tobias
full_name: Winkler, Tobias
last_name: Winkler
citation:
ama: Chatterjee K, Katoen JP, Mohr S, Weininger M, Winkler T. Stochastic games with
lexicographic objectives. Formal Methods in System Design. 2023. doi:10.1007/s10703-023-00411-4
apa: Chatterjee, K., Katoen, J. P., Mohr, S., Weininger, M., & Winkler, T. (2023).
Stochastic games with lexicographic objectives. Formal Methods in System Design.
Springer Nature. https://doi.org/10.1007/s10703-023-00411-4
chicago: Chatterjee, Krishnendu, Joost P Katoen, Stefanie Mohr, Maximilian Weininger,
and Tobias Winkler. “Stochastic Games with Lexicographic Objectives.” Formal
Methods in System Design. Springer Nature, 2023. https://doi.org/10.1007/s10703-023-00411-4.
ieee: K. Chatterjee, J. P. Katoen, S. Mohr, M. Weininger, and T. Winkler, “Stochastic
games with lexicographic objectives,” Formal Methods in System Design.
Springer Nature, 2023.
ista: Chatterjee K, Katoen JP, Mohr S, Weininger M, Winkler T. 2023. Stochastic
games with lexicographic objectives. Formal Methods in System Design.
mla: Chatterjee, Krishnendu, et al. “Stochastic Games with Lexicographic Objectives.”
Formal Methods in System Design, Springer Nature, 2023, doi:10.1007/s10703-023-00411-4.
short: K. Chatterjee, J.P. Katoen, S. Mohr, M. Weininger, T. Winkler, Formal Methods
in System Design (2023).
date_created: 2023-03-19T23:00:59Z
date_published: 2023-03-08T00:00:00Z
date_updated: 2023-10-03T11:36:13Z
day: '08'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/s10703-023-00411-4
ec_funded: 1
external_id:
isi:
- '000946174300001'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s10703-023-00411-4
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 25892FC0-B435-11E9-9278-68D0E5697425
grant_number: ICT15-003
name: Efficient Algorithms for Computer Aided Verification
publication: Formal Methods in System Design
publication_identifier:
eissn:
- 1572-8102
publication_status: epub_ahead
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '8272'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Stochastic games with lexicographic objectives
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
year: '2023'
...
---
_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
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doi: 10.1007/s13235-022-00425-3
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title: Where do mistakes lead? A survey of games with incompetent players
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