---
OA_place: repository
OA_type: green
_id: '20648'
abstract:
- lang: eng
text: Polynomial quantified entailments with existentially and universally quantified
variables arise in many problems of verification and program analysis. We present
PolyQEnt which is a tool for solving polynomial quantified entailments in which
variables on both sides of the implication are real valued or unbounded integers.
Our tool provides a unified framework for polynomial quantified entailment problems
that arise in several papers in the literature. Our experimental evaluation over
a wide range of benchmarks shows the applicability of the tool as well as its
benefits as opposed to simply using existing SMT solvers to solve such constraints.
acknowledgement: 'This work was supported by the following grants: ERC CoG 863818
(ForM-SMArt), Austrian Science Fund (FWF) 10.55776/COE12, ERC StG 101222524 (SPES),
the Ethereum Foundation Research Grant FY24-1793, and the Singapore Ministry of
Education (MOE) Academic Research Fund (AcRF) Tier 1 grant (Project ID:22-SISSMU-100).'
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- 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
- first_name: Ehsan
full_name: Kafshdar Goharshadi, Ehsan
id: 103b4fa0-896a-11ed-bdf8-87b697bef40d
last_name: Kafshdar Goharshadi
orcid: 0000-0002-8595-0587
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
orcid: 0009-0007-5253-9170
- first_name: Milad
full_name: Saadat, Milad
last_name: Saadat
- first_name: Maximilian
full_name: Seeliger, Maximilian
last_name: Seeliger
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady AK, Goharshady E, et al. PolyQEnt: A polynomial quantified
entailment solver. In: 23rd International Symposium on Automated Technology
for Verification and Analysis. Vol 16145. Springer Nature; 2025:411-424. doi:10.1007/978-3-032-08707-2_19'
apa: 'Chatterjee, K., Goharshady, A. K., Goharshady, E., Karrabi, M., Saadat, M.,
Seeliger, M., & Zikelic, D. (2025). PolyQEnt: A polynomial quantified entailment
solver. In 23rd International Symposium on Automated Technology for Verification
and Analysis (Vol. 16145, pp. 411–424). Bengaluru, India: Springer Nature.
https://doi.org/10.1007/978-3-032-08707-2_19'
chicago: 'Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Ehsan Goharshady, Mehrdad
Karrabi, Milad Saadat, Maximilian Seeliger, and Dorde Zikelic. “PolyQEnt: A Polynomial
Quantified Entailment Solver.” In 23rd International Symposium on Automated
Technology for Verification and Analysis, 16145:411–24. Springer Nature, 2025.
https://doi.org/10.1007/978-3-032-08707-2_19.'
ieee: 'K. Chatterjee et al., “PolyQEnt: A polynomial quantified entailment
solver,” in 23rd International Symposium on Automated Technology for Verification
and Analysis, Bengaluru, India, 2025, vol. 16145, pp. 411–424.'
ista: 'Chatterjee K, Goharshady AK, Goharshady E, Karrabi M, Saadat M, Seeliger
M, Zikelic D. 2025. PolyQEnt: A polynomial quantified entailment solver. 23rd
International Symposium on Automated Technology for Verification and Analysis.
ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 16145, 411–424.'
mla: 'Chatterjee, Krishnendu, et al. “PolyQEnt: A Polynomial Quantified Entailment
Solver.” 23rd International Symposium on Automated Technology for Verification
and Analysis, vol. 16145, Springer Nature, 2025, pp. 411–24, doi:10.1007/978-3-032-08707-2_19.'
short: K. Chatterjee, A.K. Goharshady, E. Goharshady, M. Karrabi, M. Saadat, M.
Seeliger, D. Zikelic, in:, 23rd International Symposium on Automated Technology
for Verification and Analysis, Springer Nature, 2025, pp. 411–424.
conference:
end_date: 2025-10-31
location: Bengaluru, India
name: 'ATVA: Automated Technology for Verification and Analysis'
start_date: 2025-10-27
corr_author: '1'
date_created: 2025-11-16T23:01:24Z
date_published: 2025-10-26T00:00:00Z
date_updated: 2025-11-24T13:11:10Z
day: '26'
department:
- _id: KrCh
doi: 10.1007/978-3-032-08707-2_19
ec_funded: 1
external_id:
arxiv:
- '2408.03796'
intvolume: ' 16145'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2408.03796
month: '10'
oa: 1
oa_version: Preprint
page: 411-424
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 23rd International Symposium on Automated Technology for Verification
and Analysis
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783032087065'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'PolyQEnt: A polynomial quantified entailment solver'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 16145
year: '2025'
...
---
OA_place: repository
OA_type: green
_id: '19667'
abstract:
- lang: eng
text: The problem of checking satisfiability of linear real arithmetic (LRA) and
non-linear real arithmetic (NRA) formulas has broad applications, in particular,
they are at the heart of logic-related applications such as logic for artificial
intelligence, program analysis, etc. While there has been much work on checking
satisfiability of unquantified LRA and NRA formulas, the problem of checking satisfiability
of quantified LRA and NRA formulas remains a significant challenge. The main bottleneck
in the existing methods is a computationally expensive quantifier elimination
step. In this work, we propose a novel method for efficient quantifier elimination
in quantified LRA and NRA formulas. We propose a template-based Skolemization
approach, where we automatically synthesize linear/polynomial Skolem functions
in order to eliminate quantifiers in the formula. The key technical ingredient
in our approach are Positivstellensätze theorems from algebraic geometry, which
allow for an efficient manipulation of polynomial inequalities. Our method offers
a range of appealing theoretical properties combined with a strong practical performance.
On the theory side, our method is sound, semi-complete, and runs in subexponential
time and polynomial space, as opposed to existing sound and complete quantifier
elimination methods that run in doubly-exponential time and at least exponential
space. On the practical side, our experiments show superior performance compared
to state of the art SMT solvers in terms of the number of solved instances and
runtime, both on LRA and on NRA benchmarks.
acknowledgement: This work was partially funded by ERC CoG 863818 (ForM-SMArt) and
Austrian Science Fund (FWF) 10.55776/COE12.
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Ehsan
full_name: Kafshdar Goharshadi, Ehsan
id: 103b4fa0-896a-11ed-bdf8-87b697bef40d
last_name: Kafshdar Goharshadi
orcid: 0000-0002-8595-0587
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
orcid: 0009-0007-5253-9170
- first_name: Harshit J.
full_name: Motwani, Harshit J.
last_name: Motwani
- first_name: Maximilian
full_name: Seeliger, Maximilian
last_name: Seeliger
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady E, Karrabi M, Motwani HJ, Seeliger M, Zikelic D.
Quantified linear and polynomial arithmetic satisfiability via template-based
skolemization. In: Proceedings of the 39th AAAI Conference on Artificial Intelligence.
Vol 39. Association for the Advancement of Artificial Intelligence; 2025:11158-11166.
doi:10.1609/aaai.v39i11.33213'
apa: 'Chatterjee, K., Goharshady, E., Karrabi, M., Motwani, H. J., Seeliger, M.,
& Zikelic, D. (2025). Quantified linear and polynomial arithmetic satisfiability
via template-based skolemization. In Proceedings of the 39th AAAI Conference
on Artificial Intelligence (Vol. 39, pp. 11158–11166). Philadelphia, PA, United
States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v39i11.33213'
chicago: Chatterjee, Krishnendu, Ehsan Goharshady, Mehrdad Karrabi, Harshit J. Motwani,
Maximilian Seeliger, and Dorde Zikelic. “Quantified Linear and Polynomial Arithmetic
Satisfiability via Template-Based Skolemization.” In Proceedings of the 39th
AAAI Conference on Artificial Intelligence, 39:11158–66. Association for the
Advancement of Artificial Intelligence, 2025. https://doi.org/10.1609/aaai.v39i11.33213.
ieee: K. Chatterjee, E. Goharshady, M. Karrabi, H. J. Motwani, M. Seeliger, and
D. Zikelic, “Quantified linear and polynomial arithmetic satisfiability via template-based
skolemization,” in Proceedings of the 39th AAAI Conference on Artificial Intelligence,
Philadelphia, PA, United States, 2025, vol. 39, no. 11, pp. 11158–11166.
ista: 'Chatterjee K, Goharshady E, Karrabi M, Motwani HJ, Seeliger M, Zikelic D.
2025. Quantified linear and polynomial arithmetic satisfiability via template-based
skolemization. Proceedings of the 39th AAAI Conference on Artificial Intelligence.
AAAI: Conference on Artificial Intelligence vol. 39, 11158–11166.'
mla: Chatterjee, Krishnendu, et al. “Quantified Linear and Polynomial Arithmetic
Satisfiability via Template-Based Skolemization.” Proceedings of the 39th AAAI
Conference on Artificial Intelligence, vol. 39, no. 11, Association for the
Advancement of Artificial Intelligence, 2025, pp. 11158–66, doi:10.1609/aaai.v39i11.33213.
short: K. Chatterjee, E. Goharshady, M. Karrabi, H.J. Motwani, M. Seeliger, D. Zikelic,
in:, Proceedings of the 39th AAAI Conference on Artificial Intelligence, Association
for the Advancement of Artificial Intelligence, 2025, pp. 11158–11166.
conference:
end_date: 2025-03-04
location: Philadelphia, PA, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2025-02-25
corr_author: '1'
date_created: 2025-05-11T22:02:39Z
date_published: 2025-04-11T00:00:00Z
date_updated: 2026-02-16T12:24:47Z
day: '11'
department:
- _id: KrCh
doi: 10.1609/aaai.v39i11.33213
ec_funded: 1
external_id:
arxiv:
- '2412.16226'
intvolume: ' 39'
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2412.16226
month: '04'
oa: 1
oa_version: Preprint
page: 11158-11166
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the 39th AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
issn:
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantified linear and polynomial arithmetic satisfiability via template-based
skolemization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 39
year: '2025'
...
---
_id: '18155'
abstract:
- lang: eng
text: We study the classical problem of verifying programs with respect to formal
specifications given in the linear temporal logic (LTL). We first present novel
sound and complete witnesses for LTL verification over imperative programs. Our
witnesses are applicable to both verification (proving) and refutation (finding
bugs) settings. We then consider LTL formulas in which atomic propositions can
be polynomial constraints and turn our focus to polynomial arithmetic programs,
i.e. programs in which every assignment and guard consists only of polynomial
expressions. For this setting, we provide an efficient algorithm to automatically
synthesize such LTL witnesses. Our synthesis procedure is both sound and semi-complete.
Finally, we present experimental results demonstrating the effectiveness of our
approach and that it can handle programs which were beyond the reach of previous
state-of-the-art tools.
acknowledgement: This work was supported in part by the ERC-2020-CoG 863818 (FoRM-SMArt)
and the Hong Kong Research Grants Council ECS Project Number 26208122.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
arxiv: 1
author:
- 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
- first_name: Ehsan
full_name: Goharshady, Ehsan
last_name: Goharshady
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady AK, Goharshady E, Karrabi M, Zikelic D. Sound and complete
witnesses for template-based verification of LTL properties on polynomial programs.
In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in
Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 14933. Springer
Nature; 2024:600-619. doi:10.1007/978-3-031-71162-6_31'
apa: 'Chatterjee, K., Goharshady, A. K., Goharshady, E., Karrabi, M., & Zikelic,
D. (2024). Sound and complete witnesses for template-based verification of LTL
properties on polynomial programs. In Lecture Notes in Computer Science (including
subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(Vol. 14933, pp. 600–619). Milan, Italy: Springer Nature. https://doi.org/10.1007/978-3-031-71162-6_31'
chicago: Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Ehsan Goharshady, Mehrdad
Karrabi, and Dorde Zikelic. “Sound and Complete Witnesses for Template-Based Verification
of LTL Properties on Polynomial Programs.” In Lecture Notes in Computer Science
(Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes
in Bioinformatics), 14933:600–619. Springer Nature, 2024. https://doi.org/10.1007/978-3-031-71162-6_31.
ieee: K. Chatterjee, A. K. Goharshady, E. Goharshady, M. Karrabi, and D. Zikelic,
“Sound and complete witnesses for template-based verification of LTL properties
on polynomial programs,” in Lecture Notes in Computer Science (including subseries
Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
Milan, Italy, 2024, vol. 14933, pp. 600–619.
ista: 'Chatterjee K, Goharshady AK, Goharshady E, Karrabi M, Zikelic D. 2024. Sound
and complete witnesses for template-based verification of LTL properties on polynomial
programs. Lecture Notes in Computer Science (including subseries Lecture Notes
in Artificial Intelligence and Lecture Notes in Bioinformatics). FM: Formal Methods,
LNCS, vol. 14933, 600–619.'
mla: Chatterjee, Krishnendu, et al. “Sound and Complete Witnesses for Template-Based
Verification of LTL Properties on Polynomial Programs.” Lecture Notes in Computer
Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture
Notes in Bioinformatics), vol. 14933, Springer Nature, 2024, pp. 600–19, doi:10.1007/978-3-031-71162-6_31.
short: K. Chatterjee, A.K. Goharshady, E. Goharshady, M. Karrabi, D. Zikelic, in:,
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial
Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2024, pp.
600–619.
conference:
end_date: 2024-09-13
location: Milan, Italy
name: 'FM: Formal Methods'
start_date: 2024-09-09
corr_author: '1'
date_created: 2024-09-29T22:01:37Z
date_published: 2024-09-11T00:00:00Z
date_updated: 2025-09-08T09:51:34Z
day: '11'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-71162-6_31
ec_funded: 1
external_id:
arxiv:
- '2403.05386'
isi:
- '001336893300031'
file:
- access_level: open_access
checksum: 223845be9e754681ee218866827c95e7
content_type: application/pdf
creator: dernst
date_created: 2024-10-01T09:56:54Z
date_updated: 2024-10-01T09:56:54Z
file_id: '18165'
file_name: 2024_LNCS_Chatterjee.pdf
file_size: 650495
relation: main_file
success: 1
file_date_updated: 2024-10-01T09:56:54Z
has_accepted_license: '1'
intvolume: ' 14933'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '09'
oa: 1
oa_version: Published Version
page: 600-619
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Lecture Notes in Computer Science (including subseries Lecture Notes
in Artificial Intelligence and Lecture Notes in Bioinformatics)
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031711619'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sound and complete witnesses for template-based verification of LTL properties
on polynomial programs
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 14933
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18160'
abstract:
- lang: eng
text: 'Markov decision processes (MDPs) provide a standard framework for sequential
decision making under uncertainty. However, MDPs do not take uncertainty in transition
probabilities into account. Robust Markov decision processes (RMDPs) address this
shortcoming of MDPs by assigning to each transition an uncertainty set rather
than a single probability value. In this work, we consider polytopic RMDPs in
which all uncertainty sets are polytopes and study the problem of solving long-run
average reward polytopic RMDPs. We present a novel perspective on this problem
and show that it can be reduced to solving long-run average reward turn-based
stochastic games with finite state and action spaces. This reduction allows us
to derive several important consequences that were hitherto not known to hold
for polytopic RMDPs. First, we derive new computational complexity bounds for
solving long-run average reward polytopic RMDPs, showing for the first time that
the threshold decision problem for them is in NP∩CONP and that they admit a randomized
algorithm with sub-exponential expected runtime. Second, we present Robust Polytopic
Policy Iteration (RPPI), a novel policy iteration algorithm for solving long-run
average reward polytopic RMDPs. Our experimental evaluation shows that RPPI is
much more efficient in solving long-run average reward polytopic RMDPs compared
to state-of-the-art methods based on value iteration. '
acknowledgement: "This work was supported in part by the ERC-2020-CoG 863818 (FoRM-SMArt)
and the Czech Science Foundation\r\ngrant no. GA23-06963S."
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Ehsan
full_name: Kafshdar Goharshadi, Ehsan
id: 103b4fa0-896a-11ed-bdf8-87b697bef40d
last_name: Kafshdar Goharshadi
orcid: 0000-0002-8595-0587
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
- first_name: Petr
full_name: Novotný, Petr
id: 3CC3B868-F248-11E8-B48F-1D18A9856A87
last_name: Novotný
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady E, Karrabi M, Novotný P, Zikelic D. Solving long-run
average reward robust MDPs via stochastic games. In: 33rd International Joint
Conference on Artificial Intelligence. International Joint Conferences on
Artificial Intelligence; 2024:6707-6715. doi:10.24963/ijcai.2024/741'
apa: 'Chatterjee, K., Goharshady, E., Karrabi, M., Novotný, P., & Zikelic, D.
(2024). Solving long-run average reward robust MDPs via stochastic games. In 33rd
International Joint Conference on Artificial Intelligence (pp. 6707–6715).
Jeju, South Korea: International Joint Conferences on Artificial Intelligence.
https://doi.org/10.24963/ijcai.2024/741'
chicago: Chatterjee, Krishnendu, Ehsan Goharshady, Mehrdad Karrabi, Petr Novotný,
and Dorde Zikelic. “Solving Long-Run Average Reward Robust MDPs via Stochastic
Games.” In 33rd International Joint Conference on Artificial Intelligence,
6707–15. International Joint Conferences on Artificial Intelligence, 2024. https://doi.org/10.24963/ijcai.2024/741.
ieee: K. Chatterjee, E. Goharshady, M. Karrabi, P. Novotný, and D. Zikelic, “Solving
long-run average reward robust MDPs via stochastic games,” in 33rd International
Joint Conference on Artificial Intelligence, Jeju, South Korea, 2024, pp.
6707–6715.
ista: 'Chatterjee K, Goharshady E, Karrabi M, Novotný P, Zikelic D. 2024. Solving
long-run average reward robust MDPs via stochastic games. 33rd International Joint
Conference on Artificial Intelligence. IJCAI: International Joint Conference on
Artificial Intelligence, 6707–6715.'
mla: Chatterjee, Krishnendu, et al. “Solving Long-Run Average Reward Robust MDPs
via Stochastic Games.” 33rd International Joint Conference on Artificial Intelligence,
International Joint Conferences on Artificial Intelligence, 2024, pp. 6707–15,
doi:10.24963/ijcai.2024/741.
short: K. Chatterjee, E. Goharshady, M. Karrabi, P. Novotný, D. Zikelic, in:, 33rd
International Joint Conference on Artificial Intelligence, International Joint
Conferences on Artificial Intelligence, 2024, pp. 6707–6715.
conference:
end_date: 2024-08-09
location: Jeju, South Korea
name: 'IJCAI: International Joint Conference on Artificial Intelligence'
start_date: 2024-08-03
corr_author: '1'
date_created: 2024-09-29T22:01:39Z
date_published: 2024-09-01T00:00:00Z
date_updated: 2025-04-14T07:52:46Z
day: '01'
department:
- _id: KrCh
doi: 10.24963/ijcai.2024/741
ec_funded: 1
external_id:
arxiv:
- '2312.13912'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2312.13912
month: '09'
oa: 1
oa_version: Preprint
page: 6707-6715
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 33rd International Joint Conference on Artificial Intelligence
publication_identifier:
isbn:
- '9781956792041'
issn:
- 1045-0823
publication_status: published
publisher: International Joint Conferences on Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Solving long-run average reward robust MDPs via stochastic games
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
_id: '17328'
abstract:
- lang: eng
text: "We study selfish mining attacks in longest-chain blockchains like Bitcoin,
but where the proof of work is replaced with efficient proof systems - like proofs
of stake or proofs of space - and consider the problem of computing an optimal
selfish mining attack which maximizes expected relative revenue of the adversary,
thus minimizing the chain quality. To this end, we propose a novel selfish mining
attack that aims to maximize this objective and formally model the attack as a
Markov decision process (MDP). We then present a formal analysis procedure which
computes an ϵ-tight lower bound on the optimal expected relative revenue in the
MDP and a strategy that achieves this ϵ-tight lower bound, where ϵ > 0 may be
any specified precision. Our analysis is fully automated and provides formal guarantees
on the correctness. We evaluate our selfish mining attack and observe that it
achieves superior expected relative revenue compared to two considered baselines.\r\nIn
concurrent work [Sarenche FC'24] does an automated analysis on selfish mining
in predictable longest-chain blockchains based on efficient proof systems. Predictable
means the randomness for the challenges is fixed for many blocks (as used e.g.,
in Ouroboros), while we consider unpredictable (Bitcoin-like) chains where the
challenge is derived from the previous block."
acknowledgement: "This work was supported in part by the ERC-2020-CoG 863818 (FoRM-SMArt)
grant and the MOE-T2EP20122-0014 (Data-Driven Distributed Algorithms) grant.\r\n"
article_processing_charge: Yes (via OA deal)
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Amirali
full_name: Ebrahimzadeh, Amirali
last_name: Ebrahimzadeh
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
- first_name: Michelle X
full_name: Yeo, Michelle X
id: 2D82B818-F248-11E8-B48F-1D18A9856A87
last_name: Yeo
orcid: 0009-0001-3676-4809
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Ebrahimzadeh A, Karrabi M, Pietrzak KZ, Yeo MX, Zikelic D. Fully
automated selfish mining analysis in efficient proof systems blockchains. In:
Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed
Computing. Association for Computing Machinery; 2024:268-278. doi:10.1145/3662158.3662769'
apa: 'Chatterjee, K., Ebrahimzadeh, A., Karrabi, M., Pietrzak, K. Z., Yeo, M. X.,
& Zikelic, D. (2024). Fully automated selfish mining analysis in efficient
proof systems blockchains. In Proceedings of the 43rd Annual ACM Symposium
on Principles of Distributed Computing (pp. 268–278). Nantes, France: Association
for Computing Machinery. https://doi.org/10.1145/3662158.3662769'
chicago: Chatterjee, Krishnendu, Amirali Ebrahimzadeh, Mehrdad Karrabi, Krzysztof
Z Pietrzak, Michelle X Yeo, and Dorde Zikelic. “Fully Automated Selfish Mining
Analysis in Efficient Proof Systems Blockchains.” In Proceedings of the 43rd
Annual ACM Symposium on Principles of Distributed Computing, 268–78. Association
for Computing Machinery, 2024. https://doi.org/10.1145/3662158.3662769.
ieee: K. Chatterjee, A. Ebrahimzadeh, M. Karrabi, K. Z. Pietrzak, M. X. Yeo, and
D. Zikelic, “Fully automated selfish mining analysis in efficient proof systems
blockchains,” in Proceedings of the 43rd Annual ACM Symposium on Principles
of Distributed Computing, Nantes, France, 2024, pp. 268–278.
ista: 'Chatterjee K, Ebrahimzadeh A, Karrabi M, Pietrzak KZ, Yeo MX, Zikelic D.
2024. Fully automated selfish mining analysis in efficient proof systems blockchains. Proceedings
of the 43rd Annual ACM Symposium on Principles of Distributed Computing. PODC:
Symposium on Principles of Distributed Computing, 268–278.'
mla: Chatterjee, Krishnendu, et al. “Fully Automated Selfish Mining Analysis in
Efficient Proof Systems Blockchains.” Proceedings of the 43rd Annual ACM Symposium
on Principles of Distributed Computing, Association for Computing Machinery,
2024, pp. 268–78, doi:10.1145/3662158.3662769.
short: K. Chatterjee, A. Ebrahimzadeh, M. Karrabi, K.Z. Pietrzak, M.X. Yeo, D. Zikelic,
in:, Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed
Computing, Association for Computing Machinery, 2024, pp. 268–278.
conference:
end_date: 2024-06-21
location: Nantes, France
name: 'PODC: Symposium on Principles of Distributed Computing'
start_date: 2024-06-17
corr_author: '1'
date_created: 2024-07-28T22:01:10Z
date_published: 2024-06-17T00:00:00Z
date_updated: 2025-04-14T07:52:47Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
- _id: KrPi
doi: 10.1145/3662158.3662769
ec_funded: 1
external_id:
arxiv:
- '2405.04420'
file:
- access_level: open_access
checksum: 6122bd97b42751ff81c452a19970f67d
content_type: application/pdf
creator: dernst
date_created: 2024-07-29T07:18:12Z
date_updated: 2024-07-29T07:18:12Z
file_id: '17334'
file_name: 2024_ACM_Chatterjee.pdf
file_size: 832034
relation: main_file
success: 1
file_date_updated: 2024-07-29T07:18:12Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 268-278
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: ' Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed
Computing'
publication_identifier:
isbn:
- '9798400706684'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Fully automated selfish mining analysis in efficient proof systems blockchains
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
year: '2024'
...
---
_id: '17329'
abstract:
- lang: eng
text: 'We initiate the study of game dynamics in the population protocol model:
n agents each maintain a current local strategy and interact in pairs uniformly
at random. Upon each interaction, the agents play a two-person game and receive
a payoff from an underlying utility function, and they can subsequently update
their strategies according to a fixed local algorithm. In this setting, we ask
how the distribution over agent strategies evolves over a sequence of interactions,
and we introduce a new distributional equilibrium concept to quantify the quality
of such distributions. As an initial example, we study a class of repeated prisoner''s
dilemma games, and we consider a family of simple local update algorithms that
yield non-trivial dynamics over the distribution of agent strategies. We show
that these dynamics are related to a new class of high-dimensional Ehrenfest random
walks, and we derive exact characterizations of their stationary distributions,
bounds on their mixing times, and prove their convergence to approximate distributional
equilibria. Our results highlight trade-offs between the local state space of
each agent, and the convergence rate and approximation factor of the underlying
dynamics. Our approach opens the door towards the further characterization of
equilibrium computation for other classes of games and dynamics in the population
setting.'
acknowledgement: This work was supported in part by the ERC-2020-CoG 863818 (FoRM-SMArt)
grant. We thank James Aspnes and Thomas Sauerwald for several helpful discussions
on Ehrenfest random walks.
article_processing_charge: Yes (via OA deal)
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Mehrdad
full_name: Karrabi, Mehrdad
id: 67638922-f394-11eb-9cf6-f20423e08757
last_name: Karrabi
- first_name: John M
full_name: Lazarsfeld, John M
id: 17ce3656-183e-11ef-84c3-8932383e1b23
last_name: Lazarsfeld
citation:
ama: 'Alistarh D-A, Chatterjee K, Karrabi M, Lazarsfeld JM. Game dynamics and equilibrium
computation in the population protocol model. In: Proceedings of the 43rd Annual
ACM Symposium on Principles of Distributed Computing. Association for Computing
Machinery; 2024:40-49. doi:10.1145/3662158.3662768'
apa: 'Alistarh, D.-A., Chatterjee, K., Karrabi, M., & Lazarsfeld, J. M. (2024).
Game dynamics and equilibrium computation in the population protocol model. In
Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed Computing
(pp. 40–49). Nantes, France: Association for Computing Machinery. https://doi.org/10.1145/3662158.3662768'
chicago: Alistarh, Dan-Adrian, Krishnendu Chatterjee, Mehrdad Karrabi, and John
M Lazarsfeld. “Game Dynamics and Equilibrium Computation in the Population Protocol
Model.” In Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed
Computing, 40–49. Association for Computing Machinery, 2024. https://doi.org/10.1145/3662158.3662768.
ieee: D.-A. Alistarh, K. Chatterjee, M. Karrabi, and J. M. Lazarsfeld, “Game dynamics
and equilibrium computation in the population protocol model,” in Proceedings
of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Nantes,
France, 2024, pp. 40–49.
ista: 'Alistarh D-A, Chatterjee K, Karrabi M, Lazarsfeld JM. 2024. Game dynamics
and equilibrium computation in the population protocol model. Proceedings of the
43rd Annual ACM Symposium on Principles of Distributed Computing. PODC: Symposium
on Principles of Distributed Computing, 40–49.'
mla: Alistarh, Dan-Adrian, et al. “Game Dynamics and Equilibrium Computation in
the Population Protocol Model.” Proceedings of the 43rd Annual ACM Symposium
on Principles of Distributed Computing, Association for Computing Machinery,
2024, pp. 40–49, doi:10.1145/3662158.3662768.
short: D.-A. Alistarh, K. Chatterjee, M. Karrabi, J.M. Lazarsfeld, in:, Proceedings
of the 43rd Annual ACM Symposium on Principles of Distributed Computing, Association
for Computing Machinery, 2024, pp. 40–49.
conference:
end_date: 2024-06-21
location: Nantes, France
name: 'PODC: Symposium on Principles of Distributed Computing'
start_date: 2024-06-17
corr_author: '1'
date_created: 2024-07-28T22:01:10Z
date_published: 2024-06-17T00:00:00Z
date_updated: 2025-04-14T07:52:47Z
day: '17'
ddc:
- '000'
department:
- _id: DaAl
- _id: KrCh
doi: 10.1145/3662158.3662768
ec_funded: 1
file:
- access_level: open_access
checksum: 65a40437f83373fa79dd999d5287509e
content_type: application/pdf
creator: dernst
date_created: 2024-07-29T07:37:31Z
date_updated: 2024-07-29T07:37:31Z
file_id: '17335'
file_name: 2024_ACMPODC_Alistarh.pdf
file_size: 750908
relation: main_file
success: 1
file_date_updated: 2024-07-29T07:37:31Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 40-49
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the 43rd Annual ACM Symposium on Principles of Distributed
Computing
publication_identifier:
isbn:
- '9798400706684'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Game dynamics and equilibrium computation in the population protocol model
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
year: '2024'
...