---
_id: '11459'
abstract:
- lang: eng
text: 'We present a novel approach to differential cost analysis that, given a program
revision, attempts to statically bound the difference in resource usage, or cost,
between the two program versions. Differential cost analysis is particularly interesting
because of the many compelling applications for it, such as detecting resource-use
regressions at code-review time or proving the absence of certain side-channel
vulnerabilities. One prior approach to differential cost analysis is to apply
relational reasoning that conceptually constructs a product program on which one
can over-approximate the difference in costs between the two program versions.
However, a significant challenge in any relational approach is effectively aligning
the program versions to get precise results. In this paper, our key insight is
that we can avoid the need for and the limitations of program alignment if, instead,
we bound the difference of two cost-bound summaries rather than directly bounding
the concrete cost difference. In particular, our method computes a threshold value
for the maximal difference in cost between two program versions simultaneously
using two kinds of cost-bound summaries---a potential function that evaluates
to an upper bound for the cost incurred in the first program and an anti-potential
function that evaluates to a lower bound for the cost incurred in the second.
Our method has a number of desirable properties: it can be fully automated, it
allows optimizing the threshold value on relative cost, it is suitable for programs
that are not syntactically similar, and it supports non-determinism. We have evaluated
an implementation of our approach on a number of program pairs collected from
the literature, and we find that our method computes tight threshold values on
relative cost in most examples.'
acknowledgement: "We thank Shaun Willows, Thomas Lugnet, and the Living Room Application
Vending team for suggesting threshold\r\nbounds as a developer-friendly way to interact
with a differential cost analyzer, and we thank Jim Christy, Daniel\r\nSchoepe,
and the Prime Video Automated Reasoning team for their support and helpful suggestions
throughout the\r\nproject. We also thank Michael Emmi for feedback on an earlier
version of this paper. And finally, we thank the anonymous reviewers for their useful
feedback and Aws Albarghouthi for shepherding the final version of the paper. Ðorđe
Žikelić was also partially supported by ERC CoG 863818 (FoRM-SMArt)."
article_processing_charge: No
author:
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
- first_name: Bor-Yuh Evan
full_name: Chang, Bor-Yuh Evan
last_name: Chang
- first_name: Pauline
full_name: Bolignano, Pauline
last_name: Bolignano
- first_name: Franco
full_name: Raimondi, Franco
last_name: Raimondi
citation:
ama: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. Differential cost analysis
with simultaneous potentials and anti-potentials. In: Proceedings of the 43rd
ACM SIGPLAN International Conference on Programming Language Design and Implementation.
Association for Computing Machinery; 2022:442-457. doi:10.1145/3519939.3523435'
apa: 'Zikelic, D., Chang, B.-Y. E., Bolignano, P., & Raimondi, F. (2022). Differential
cost analysis with simultaneous potentials and anti-potentials. In Proceedings
of the 43rd ACM SIGPLAN International Conference on Programming Language Design
and Implementation (pp. 442–457). San Diego, CA, United States: Association
for Computing Machinery. https://doi.org/10.1145/3519939.3523435'
chicago: Zikelic, Dorde, Bor-Yuh Evan Chang, Pauline Bolignano, and Franco Raimondi.
“Differential Cost Analysis with Simultaneous Potentials and Anti-Potentials.”
In Proceedings of the 43rd ACM SIGPLAN International Conference on Programming
Language Design and Implementation, 442–57. Association for Computing Machinery,
2022. https://doi.org/10.1145/3519939.3523435.
ieee: D. Zikelic, B.-Y. E. Chang, P. Bolignano, and F. Raimondi, “Differential cost
analysis with simultaneous potentials and anti-potentials,” in Proceedings
of the 43rd ACM SIGPLAN International Conference on Programming Language Design
and Implementation, San Diego, CA, United States, 2022, pp. 442–457.
ista: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. 2022. Differential cost analysis
with simultaneous potentials and anti-potentials. Proceedings of the 43rd ACM
SIGPLAN International Conference on Programming Language Design and Implementation.
PLDI: Programming Language Design and Implementation, 442–457.'
mla: Zikelic, Dorde, et al. “Differential Cost Analysis with Simultaneous Potentials
and Anti-Potentials.” Proceedings of the 43rd ACM SIGPLAN International Conference
on Programming Language Design and Implementation, Association for Computing
Machinery, 2022, pp. 442–57, doi:10.1145/3519939.3523435.
short: D. Zikelic, B.-Y.E. Chang, P. Bolignano, F. Raimondi, in:, Proceedings of
the 43rd ACM SIGPLAN International Conference on Programming Language Design and
Implementation, Association for Computing Machinery, 2022, pp. 442–457.
conference:
end_date: 2022-06-17
location: San Diego, CA, United States
name: 'PLDI: Programming Language Design and Implementation'
start_date: 2022-06-13
date_created: 2022-06-21T09:26:15Z
date_published: 2022-06-09T00:00:00Z
date_updated: 2023-08-03T07:22:33Z
day: '09'
ddc:
- '000'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1145/3519939.3523435
ec_funded: 1
external_id:
arxiv:
- '2204.00870'
isi:
- '000850435600030'
file:
- access_level: open_access
checksum: 7eb915a2ca5b5ce4729321f33b2e16e1
content_type: application/pdf
creator: dernst
date_created: 2022-06-27T07:38:21Z
date_updated: 2022-06-27T07:38:21Z
file_id: '11466'
file_name: 2022_PLDI_Zikelic.pdf
file_size: 318697
relation: main_file
success: 1
file_date_updated: 2022-06-27T07:38:21Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '06'
oa: 1
oa_version: Published Version
page: 442-457
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 ACM SIGPLAN International Conference on Programming
Language Design and Implementation
publication_identifier:
isbn:
- '9781450392655'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Differential cost analysis with simultaneous potentials and anti-potentials
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2022'
...
---
_id: '12257'
abstract:
- lang: eng
text: Structural balance theory is an established framework for studying social
relationships of friendship and enmity. These relationships are modeled by a signed
network whose energy potential measures the level of imbalance, while stochastic
dynamics drives the network toward a state of minimum energy that captures social
balance. It is known that this energy landscape has local minima that can trap
socially aware dynamics, preventing it from reaching balance. Here we first study
the robustness and attractor properties of these local minima. We show that a
stochastic process can reach them from an abundance of initial states and that
some local minima cannot be escaped by mild perturbations of the network. Motivated
by these anomalies, we introduce best-edge dynamics (BED), a new plausible stochastic
process. We prove that BED always reaches balance and that it does so fast in
various interesting settings.
acknowledgement: "K.C. acknowledges support from ERC Start Grant No. (279307: Graph
Games), ERC Consolidator Grant No. (863818: ForM-SMart), and Austrian Science Fund
(FWF)\r\nGrants No. P23499-N23 and No. S11407-N23 (RiSE). This project has received
funding from the European Union’s Horizon 2020 research and innovation programme
under the Marie\r\nSkłodowska-Curie Grant Agreement No. 665385."
article_number: '034321'
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: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
- first_name: Andreas
full_name: Pavlogiannis, Andreas
id: 49704004-F248-11E8-B48F-1D18A9856A87
last_name: Pavlogiannis
orcid: 0000-0002-8943-0722
- first_name: Josef
full_name: Tkadlec, Josef
id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
last_name: Tkadlec
orcid: 0000-0002-1097-9684
citation:
ama: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. Social balance
on networks: Local minima and best-edge dynamics. Physical Review E. 2022;106(3).
doi:10.1103/physreve.106.034321'
apa: 'Chatterjee, K., Svoboda, J., Zikelic, D., Pavlogiannis, A., & Tkadlec,
J. (2022). Social balance on networks: Local minima and best-edge dynamics. Physical
Review E. American Physical Society. https://doi.org/10.1103/physreve.106.034321'
chicago: 'Chatterjee, Krishnendu, Jakub Svoboda, Dorde Zikelic, Andreas Pavlogiannis,
and Josef Tkadlec. “Social Balance on Networks: Local Minima and Best-Edge Dynamics.”
Physical Review E. American Physical Society, 2022. https://doi.org/10.1103/physreve.106.034321.'
ieee: 'K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, and J. Tkadlec, “Social
balance on networks: Local minima and best-edge dynamics,” Physical Review
E, vol. 106, no. 3. American Physical Society, 2022.'
ista: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. 2022. Social
balance on networks: Local minima and best-edge dynamics. Physical Review E. 106(3),
034321.'
mla: 'Chatterjee, Krishnendu, et al. “Social Balance on Networks: Local Minima and
Best-Edge Dynamics.” Physical Review E, vol. 106, no. 3, 034321, American
Physical Society, 2022, doi:10.1103/physreve.106.034321.'
short: K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, J. Tkadlec, Physical
Review E 106 (2022).
date_created: 2023-01-16T09:57:57Z
date_published: 2022-09-29T00:00:00Z
date_updated: 2023-08-04T09:50:44Z
day: '29'
department:
- _id: KrCh
doi: 10.1103/physreve.106.034321
ec_funded: 1
external_id:
arxiv:
- '2210.02394'
isi:
- '000870243100001'
intvolume: ' 106'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2210.02394
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '279307'
name: 'Quantitative Graph Games: Theory and Applications'
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2584A770-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 23499-N23
name: Modern Graph Algorithmic Techniques in Formal Verification
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Physical Review E
publication_identifier:
eissn:
- 2470-0053
issn:
- 2470-0045
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Social balance on networks: Local minima and best-edge dynamics'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 106
year: '2022'
...
---
_id: '12280'
abstract:
- lang: eng
text: 'In repeated interactions, players can use strategies that respond to the
outcome of previous rounds. Much of the existing literature on direct reciprocity
assumes that all competing individuals use the same strategy space. Here, we study
both learning and evolutionary dynamics of players that differ in the strategy
space they explore. We focus on the infinitely repeated donation game and compare
three natural strategy spaces: memory-1 strategies, which consider the last moves
of both players, reactive strategies, which respond to the last move of the co-player,
and unconditional strategies. These three strategy spaces differ in the memory
capacity that is needed. We compute the long term average payoff that is achieved
in a pairwise learning process. We find that smaller strategy spaces can dominate
larger ones. For weak selection, unconditional players dominate both reactive
and memory-1 players. For intermediate selection, reactive players dominate memory-1
players. Only for strong selection and low cost-to-benefit ratio, memory-1 players
dominate the others. We observe that the supergame between strategy spaces can
be a social dilemma: maximum payoff is achieved if both players explore a larger
strategy space, but smaller strategy spaces dominate.'
acknowledgement: "This work was supported by the European Research Council (https://erc.europa.eu/)\r\nCoG
863818 (ForM-SMArt) (to K.C.), and the European Research Council Starting Grant
850529: E-DIRECT (to C.H.). The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript."
article_number: e1010149
article_processing_charge: No
article_type: original
author:
- first_name: Laura
full_name: Schmid, Laura
id: 38B437DE-F248-11E8-B48F-1D18A9856A87
last_name: Schmid
orcid: 0000-0002-6978-7329
- first_name: Christian
full_name: Hilbe, Christian
id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87
last_name: Hilbe
orcid: 0000-0001-5116-955X
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Martin
full_name: Nowak, Martin
last_name: Nowak
citation:
ama: Schmid L, Hilbe C, Chatterjee K, Nowak M. Direct reciprocity between individuals
that use different strategy spaces. PLOS Computational Biology. 2022;18(6).
doi:10.1371/journal.pcbi.1010149
apa: Schmid, L., Hilbe, C., Chatterjee, K., & Nowak, M. (2022). Direct reciprocity
between individuals that use different strategy spaces. PLOS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1010149
chicago: Schmid, Laura, Christian Hilbe, Krishnendu Chatterjee, and Martin Nowak.
“Direct Reciprocity between Individuals That Use Different Strategy Spaces.” PLOS
Computational Biology. Public Library of Science, 2022. https://doi.org/10.1371/journal.pcbi.1010149.
ieee: L. Schmid, C. Hilbe, K. Chatterjee, and M. Nowak, “Direct reciprocity between
individuals that use different strategy spaces,” PLOS Computational Biology,
vol. 18, no. 6. Public Library of Science, 2022.
ista: Schmid L, Hilbe C, Chatterjee K, Nowak M. 2022. Direct reciprocity between
individuals that use different strategy spaces. PLOS Computational Biology. 18(6),
e1010149.
mla: Schmid, Laura, et al. “Direct Reciprocity between Individuals That Use Different
Strategy Spaces.” PLOS Computational Biology, vol. 18, no. 6, e1010149,
Public Library of Science, 2022, doi:10.1371/journal.pcbi.1010149.
short: L. Schmid, C. Hilbe, K. Chatterjee, M. Nowak, PLOS Computational Biology
18 (2022).
date_created: 2023-01-16T10:02:51Z
date_published: 2022-06-14T00:00:00Z
date_updated: 2023-08-04T10:27:08Z
day: '14'
ddc:
- '000'
- '570'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1010149
ec_funded: 1
external_id:
isi:
- '000843626800031'
pmid:
- '35700167'
file:
- access_level: open_access
checksum: 31b6b311b6731f1658277a9dfff6632c
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T11:28:13Z
date_updated: 2023-01-30T11:28:13Z
file_id: '12460'
file_name: 2022_PlosCompBio_Schmid.pdf
file_size: 3143222
relation: main_file
success: 1
file_date_updated: 2023-01-30T11:28:13Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '6'
keyword:
- Computational Theory and Mathematics
- Cellular and Molecular Neuroscience
- Genetics
- Molecular Biology
- Ecology
- Modeling and Simulation
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '06'
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'
publication: PLOS Computational Biology
publication_identifier:
eissn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Direct reciprocity between individuals that use different strategy spaces
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: 18
year: '2022'
...
---
_id: '9311'
abstract:
- lang: eng
text: 'Partially observable Markov decision processes (POMDPs) are standard models
for dynamic systems with probabilistic and nondeterministic behaviour in uncertain
environments. We prove that in POMDPs with long-run average objective, the decision
maker has approximately optimal strategies with finite memory. This implies notably
that approximating the long-run value is recursively enumerable, as well as a
weak continuity property of the value with respect to the transition function. '
acknowledgement: "Partially supported by Austrian Science Fund (FWF) NFN Grant No
RiSE/SHiNE S11407, by CONICYT Chile through grant PII 20150140, and by ECOS-CONICYT
through grant C15E03.\r\n"
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: Raimundo J
full_name: Saona Urmeneta, Raimundo J
id: BD1DF4C4-D767-11E9-B658-BC13E6697425
last_name: Saona Urmeneta
orcid: 0000-0001-5103-038X
- first_name: Bruno
full_name: Ziliotto, Bruno
last_name: Ziliotto
citation:
ama: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. Finite-memory strategies in POMDPs
with long-run average objectives. Mathematics of Operations Research. 2022;47(1):100-119.
doi:10.1287/moor.2020.1116
apa: Chatterjee, K., Saona Urmeneta, R. J., & Ziliotto, B. (2022). Finite-memory
strategies in POMDPs with long-run average objectives. Mathematics of Operations
Research. Institute for Operations Research and the Management Sciences. https://doi.org/10.1287/moor.2020.1116
chicago: Chatterjee, Krishnendu, Raimundo J Saona Urmeneta, and Bruno Ziliotto.
“Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics
of Operations Research. Institute for Operations Research and the Management
Sciences, 2022. https://doi.org/10.1287/moor.2020.1116.
ieee: K. Chatterjee, R. J. Saona Urmeneta, and B. Ziliotto, “Finite-memory strategies
in POMDPs with long-run average objectives,” Mathematics of Operations Research,
vol. 47, no. 1. Institute for Operations Research and the Management Sciences,
pp. 100–119, 2022.
ista: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. 2022. Finite-memory strategies
in POMDPs with long-run average objectives. Mathematics of Operations Research.
47(1), 100–119.
mla: Chatterjee, Krishnendu, et al. “Finite-Memory Strategies in POMDPs with Long-Run
Average Objectives.” Mathematics of Operations Research, vol. 47, no. 1,
Institute for Operations Research and the Management Sciences, 2022, pp. 100–19,
doi:10.1287/moor.2020.1116.
short: K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations
Research 47 (2022) 100–119.
date_created: 2021-04-08T09:33:31Z
date_published: 2022-02-01T00:00:00Z
date_updated: 2023-09-05T13:16:11Z
day: '01'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1287/moor.2020.1116
external_id:
arxiv:
- '1904.13360'
isi:
- '000731918100001'
intvolume: ' 47'
isi: 1
issue: '1'
keyword:
- Management Science and Operations Research
- General Mathematics
- Computer Science Applications
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1904.13360
month: '02'
oa: 1
oa_version: Preprint
page: 100-119
project:
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
publication: Mathematics of Operations Research
publication_identifier:
eissn:
- 1526-5471
issn:
- 0364-765X
publication_status: published
publisher: Institute for Operations Research and the Management Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Finite-memory strategies in POMDPs with long-run average objectives
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 47
year: '2022'
...
---
_id: '12170'
abstract:
- lang: eng
text: We present PET, a specialized and highly optimized framework for partial exploration
on probabilistic systems. Over the last decade, several significant advances in
the analysis of Markov decision processes employed partial exploration. In a nutshell,
this idea allows to focus computation on specific parts of the system, guided
by heuristics, while maintaining correctness. In particular, only relevant parts
of the system are constructed on demand, which in turn potentially allows to omit
constructing large parts of the system. Depending on the model, this leads to
dramatic speed-ups, in extreme cases even up to an arbitrary factor. PET unifies
several previous implementations and provides a flexible framework to easily implement
partial exploration for many further problems. Our experimental evaluation shows
significant improvements compared to the previous implementations while vastly
reducing the overhead required to add support for additional properties.
acknowledgement: We thank Pranav Ashok and Maximilian Weininger for their contributions
to spiritual predecessors of PET as well as motivating the initial development of
this tool.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
citation:
ama: 'Meggendorfer T. PET – A partial exploration tool for probabilistic verification.
In: 20th International Symposium on Automated Technology for Verification and
Analysis. Vol 13505. Springer Nature; 2022:320-326. doi:10.1007/978-3-031-19992-9_20'
apa: 'Meggendorfer, T. (2022). PET – A partial exploration tool for probabilistic
verification. In 20th International Symposium on Automated Technology for Verification
and Analysis (Vol. 13505, pp. 320–326). Virtual: Springer Nature. https://doi.org/10.1007/978-3-031-19992-9_20'
chicago: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic
Verification.” In 20th International Symposium on Automated Technology for
Verification and Analysis, 13505:320–26. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19992-9_20.
ieee: T. Meggendorfer, “PET – A partial exploration tool for probabilistic verification,”
in 20th International Symposium on Automated Technology for Verification and
Analysis, Virtual, 2022, vol. 13505, pp. 320–326.
ista: 'Meggendorfer T. 2022. PET – A partial exploration tool for probabilistic
verification. 20th International Symposium on Automated Technology for Verification
and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS,
vol. 13505, 320–326.'
mla: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic Verification.”
20th International Symposium on Automated Technology for Verification and Analysis,
vol. 13505, Springer Nature, 2022, pp. 320–26, doi:10.1007/978-3-031-19992-9_20.
short: T. Meggendorfer, in:, 20th International Symposium on Automated Technology
for Verification and Analysis, Springer Nature, 2022, pp. 320–326.
conference:
end_date: 2022-10-28
location: Virtual
name: 'ATVA: Automated Technology for Verification and Analysis'
start_date: 2022-10-25
date_created: 2023-01-12T12:11:07Z
date_published: 2022-10-21T00:00:00Z
date_updated: 2023-09-05T15:11:51Z
day: '21'
department:
- _id: KrCh
doi: 10.1007/978-3-031-19992-9_20
intvolume: ' 13505'
language:
- iso: eng
month: '10'
oa_version: None
page: 320-326
publication: 20th International Symposium on Automated Technology for Verification
and Analysis
publication_identifier:
eisbn:
- '9783031199929'
eissn:
- 1611-3349
isbn:
- '9783031199912'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: PET – A partial exploration tool for probabilistic verification
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 13505
year: '2022'
...
---
_id: '11402'
abstract:
- lang: eng
text: Fixed-horizon planning considers a weighted graph and asks to construct a
path that maximizes the sum of weights for a given time horizon T. However, in
many scenarios, the time horizon is not fixed, but the stopping time is chosen
according to some distribution such that the expected stopping time is T. If the
stopping-time distribution is not known, then to ensure robustness, the distribution
is chosen by an adversary as the worst-case scenario. A stationary plan for every
vertex always chooses the same outgoing edge. For fixed horizon or fixed stopping-time
distribution, stationary plans are not sufficient for optimality. Quite surprisingly
we show that when an adversary chooses the stopping-time distribution with expected
stopping-time T, then stationary plans are sufficient. While computing optimal
stationary plans for fixed horizon is NP-complete, we show that computing optimal
stationary plans under adversarial stopping-time distribution can be achieved
in polynomial time.
acknowledgement: This work was partially supported by Austrian Science Fund (FWF)
NFN Grant No RiSE/SHiNE S11407 and by the grant ERC CoG 863818 (ForM-SMArt).
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: Laurent
full_name: Doyen, Laurent
last_name: Doyen
citation:
ama: Chatterjee K, Doyen L. Graph planning with expected finite horizon. Journal
of Computer and System Sciences. 2022;129:1-21. doi:10.1016/j.jcss.2022.04.003
apa: Chatterjee, K., & Doyen, L. (2022). Graph planning with expected finite
horizon. Journal of Computer and System Sciences. Elsevier. https://doi.org/10.1016/j.jcss.2022.04.003
chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected
Finite Horizon.” Journal of Computer and System Sciences. Elsevier, 2022.
https://doi.org/10.1016/j.jcss.2022.04.003.
ieee: K. Chatterjee and L. Doyen, “Graph planning with expected finite horizon,”
Journal of Computer and System Sciences, vol. 129. Elsevier, pp. 1–21,
2022.
ista: Chatterjee K, Doyen L. 2022. Graph planning with expected finite horizon.
Journal of Computer and System Sciences. 129, 1–21.
mla: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected Finite
Horizon.” Journal of Computer and System Sciences, vol. 129, Elsevier,
2022, pp. 1–21, doi:10.1016/j.jcss.2022.04.003.
short: K. Chatterjee, L. Doyen, Journal of Computer and System Sciences 129 (2022)
1–21.
date_created: 2022-05-22T22:01:40Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2023-09-07T14:48:11Z
day: '01'
department:
- _id: KrCh
doi: 10.1016/j.jcss.2022.04.003
ec_funded: 1
external_id:
arxiv:
- '1802.03642'
isi:
- '000805002800001'
intvolume: ' 129'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.1802.03642'
month: '11'
oa: 1
oa_version: Preprint
page: 1-21
project:
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Journal of Computer and System Sciences
publication_identifier:
eissn:
- 1090-2724
issn:
- 0022-0000
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
record:
- id: '7402'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Graph planning with expected finite horizon
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 129
year: '2022'
...
---
_id: '12775'
abstract:
- lang: eng
text: "We consider the problem of approximating the reachability probabilities in
Markov decision processes (MDP) with uncountable (continuous) state and action
spaces. While there are algorithms that, for special classes of such MDP, provide
a sequence of approximations converging to the true value in the limit, our aim
is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs
this problem is undecidable in general, assumptions on the MDP are necessary.
Our main contribution is to identify sufficient assumptions that are as weak as
possible, thus approaching the \"boundary\" of which systems can be correctly
and reliably analyzed. To this end, we also argue why each of our assumptions
is necessary for algorithms based on processing finitely many observations.\r\nWe
present two solution variants. The first one provides converging lower bounds
under weaker assumptions than typical ones from previous works concerned with
guarantees. The second one then utilizes stronger assumptions to additionally
provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e.
yielding a sequence of approximants with known and iteratively improving precision,
converging to the true value in the limit. Besides, due to the generality of our
assumptions, our algorithms are very general templates, readily allowing for various
heuristics from literature in contrast to, e.g., a specific discretization algorithm.
Our theoretical contribution thus paves the way for future practical improvements
without sacrificing correctness guarantees."
acknowledgement: "Kush Grover: The author has been supported by the DFG research training
group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially
supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV)
and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)"
alternative_title:
- LIPIcs
article_number: '11'
article_processing_charge: No
author:
- first_name: Kush
full_name: Grover, Kush
last_name: Grover
- 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: Maimilian
full_name: Weininger, Maimilian
last_name: Weininger
citation:
ama: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for
reachability in uncountable Markov decision processes. In: 33rd International
Conference on Concurrency Theory . Vol 243. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2022. doi:10.4230/LIPIcs.CONCUR.2022.11'
apa: 'Grover, K., Kretinsky, J., Meggendorfer, T., & Weininger, M. (2022). Anytime
guarantees for reachability in uncountable Markov decision processes. In 33rd
International Conference on Concurrency Theory (Vol. 243). Warsaw, Poland:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11'
chicago: Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger.
“Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.”
In 33rd International Conference on Concurrency Theory , Vol. 243. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11.
ieee: K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees
for reachability in uncountable Markov decision processes,” in 33rd International
Conference on Concurrency Theory , Warsaw, Poland, 2022, vol. 243.
ista: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees
for reachability in uncountable Markov decision processes. 33rd International
Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs,
vol. 243, 11.'
mla: Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov
Decision Processes.” 33rd International Conference on Concurrency Theory ,
vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.CONCUR.2022.11.
short: K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International
Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022.
conference:
end_date: 2022-09-16
location: Warsaw, Poland
name: 'CONCUR: Conference on Concurrency Theory'
start_date: 2022-09-13
date_created: 2023-03-28T08:09:32Z
date_published: 2022-09-15T00:00:00Z
date_updated: 2023-09-26T10:43:30Z
day: '15'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.CONCUR.2022.11
external_id:
arxiv:
- '2008.04824'
file:
- access_level: open_access
checksum: e282e43d3ae0ba6e067b72f4583e13c0
content_type: application/pdf
creator: dernst
date_created: 2023-09-26T10:43:15Z
date_updated: 2023-09-26T10:43:15Z
file_id: '14372'
file_name: 2022_LIPIcS_Grover.pdf
file_size: 960036
relation: main_file
success: 1
file_date_updated: 2023-09-26T10:43:15Z
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intvolume: ' 243'
language:
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month: '09'
oa: 1
oa_version: Published Version
publication: '33rd International Conference on Concurrency Theory '
publication_identifier:
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Anytime guarantees for reachability in uncountable Markov decision processes
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: 243
year: '2022'
...
---
_id: '12000'
abstract:
- lang: eng
text: "We consider the quantitative problem of obtaining lower-bounds on the probability
of termination of a given non-deterministic probabilistic program. Specifically,
given a non-termination threshold p∈[0,1], we aim for certificates proving that
the program terminates with probability at least 1−p. The basic idea of our approach
is to find a terminating stochastic invariant, i.e. a subset SI of program states
such that (i) the probability of the program ever leaving SI is no more than p,
and (ii) almost-surely, the program either leaves SI or terminates.\r\n\r\nWhile
stochastic invariants are already well-known, we provide the first proof that
the idea above is not only sound, but also complete for quantitative termination
analysis. We then introduce a novel sound and complete characterization of stochastic
invariants that enables template-based approaches for easy synthesis of quantitative
termination certificates, especially in affine or polynomial forms. Finally, by
combining this idea with the existing martingale-based methods that are relatively
complete for qualitative termination analysis, we obtain the first automated,
sound, and relatively complete algorithm for quantitative termination analysis.
Notably, our completeness guarantees for quantitative termination analysis are
as strong as the best-known methods for the qualitative variant.\r\n\r\nOur prototype
implementation demonstrates the effectiveness of our approach on various probabilistic
programs. We also demonstrate that our algorithm certifies lower bounds on termination
probability for probabilistic programs that are beyond the reach of previous methods."
acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt),
the HKUST-Kaisa Joint Research Institute Project Grant HKJRI3A-055, the HKUST Startup
Grant R9272 and the European Union’s Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
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: 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: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. Sound and complete
certificates for auantitative termination analysis of probabilistic programs.
In: Proceedings of the 34th International Conference on Computer Aided Verification.
Vol 13371. Springer; 2022:55-78. doi:10.1007/978-3-031-13185-1_4'
apa: 'Chatterjee, K., Goharshady, A. K., Meggendorfer, T., & Zikelic, D. (2022).
Sound and complete certificates for auantitative termination analysis of probabilistic
programs. In Proceedings of the 34th International Conference on Computer Aided
Verification (Vol. 13371, pp. 55–78). Haifa, Israel: Springer. https://doi.org/10.1007/978-3-031-13185-1_4'
chicago: Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Tobias Meggendorfer,
and Dorde Zikelic. “Sound and Complete Certificates for Auantitative Termination
Analysis of Probabilistic Programs.” In Proceedings of the 34th International
Conference on Computer Aided Verification, 13371:55–78. Springer, 2022. https://doi.org/10.1007/978-3-031-13185-1_4.
ieee: K. Chatterjee, A. K. Goharshady, T. Meggendorfer, and D. Zikelic, “Sound and complete
certificates for auantitative termination analysis of probabilistic programs,”
in Proceedings of the 34th International Conference on Computer Aided Verification,
Haifa, Israel, 2022, vol. 13371, pp. 55–78.
ista: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. 2022. Sound and complete
certificates for auantitative termination analysis of probabilistic programs.
Proceedings of the 34th International Conference on Computer Aided Verification.
CAV: Computer Aided Verification, LNCS, vol. 13371, 55–78.'
mla: Chatterjee, Krishnendu, et al. “Sound and Complete Certificates for Auantitative
Termination Analysis of Probabilistic Programs.” Proceedings of the 34th International
Conference on Computer Aided Verification, vol. 13371, Springer, 2022, pp.
55–78, doi:10.1007/978-3-031-13185-1_4.
short: K. Chatterjee, A.K. Goharshady, T. Meggendorfer, D. Zikelic, in:, Proceedings
of the 34th International Conference on Computer Aided Verification, Springer,
2022, pp. 55–78.
conference:
end_date: 2022-08-10
location: Haifa, Israel
name: 'CAV: Computer Aided Verification'
start_date: 2022-08-07
date_created: 2022-08-28T22:02:02Z
date_published: 2022-08-07T00:00:00Z
date_updated: 2023-11-30T10:55:37Z
day: '07'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-13185-1_4
ec_funded: 1
external_id:
isi:
- '000870304500004'
file:
- access_level: open_access
checksum: 24e0f810ec52735a90ade95198bc641d
content_type: application/pdf
creator: alisjak
date_created: 2022-08-29T09:17:01Z
date_updated: 2022-08-29T09:17:01Z
file_id: '12003'
file_name: 2022_LNCS_Chatterjee.pdf
file_size: 505094
relation: main_file
success: 1
file_date_updated: 2022-08-29T09:17:01Z
has_accepted_license: '1'
intvolume: ' 13371'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 55-78
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 34th International Conference on Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031131844'
issn:
- 0302-9743
publication_status: published
publisher: Springer
quality_controlled: '1'
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Sound and complete certificates for auantitative termination analysis of probabilistic
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13371
year: '2022'
...
---
_id: '12511'
abstract:
- lang: eng
text: "We consider the problem of formally verifying almost-sure (a.s.) asymptotic
stability in discrete-time nonlinear stochastic control systems. While verifying
stability in deterministic control systems is extensively studied in the literature,
verifying stability in stochastic control systems is an open problem. The few
existing works on this topic either consider only specialized forms of stochasticity
or make restrictive assumptions on the system, rendering them inapplicable to
learning algorithms with neural network policies. \r\n In this work, we present
an approach for general nonlinear stochastic control problems with two novel aspects:
(a) instead of classical stochastic extensions of Lyapunov functions, we use ranking
supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present
a method for learning neural network RSMs. \r\n We prove that our approach guarantees
a.s. asymptotic stability of the system and\r\n provides the first method to obtain
bounds on the stabilization time, which stochastic Lyapunov functions do not.\r\n
Finally, we validate our approach experimentally on a set of nonlinear stochastic
reinforcement learning environments with neural network policies."
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme\r\nunder the Marie Skłodowska-Curie Grant Agreement No. 665385."
article_processing_charge: No
article_type: original
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in
stochastic control systems via neural network supermartingales. Proceedings
of the AAAI Conference on Artificial Intelligence. 2022;36(7):7326-7336. doi:10.1609/aaai.v36i7.20695
apa: Lechner, M., Zikelic, D., Chatterjee, K., & Henzinger, T. A. (2022). Stability
verification in stochastic control systems via neural network supermartingales.
Proceedings of the AAAI Conference on Artificial Intelligence. Association
for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i7.20695
chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger.
“Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.”
Proceedings of the AAAI Conference on Artificial Intelligence. Association
for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i7.20695.
ieee: M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification
in stochastic control systems via neural network supermartingales,” Proceedings
of the AAAI Conference on Artificial Intelligence, vol. 36, no. 7. Association
for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.
ista: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification
in stochastic control systems via neural network supermartingales. Proceedings
of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336.
mla: Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems
via Neural Network Supermartingales.” Proceedings of the AAAI Conference on
Artificial Intelligence, vol. 36, no. 7, Association for the Advancement of
Artificial Intelligence, 2022, pp. 7326–36, doi:10.1609/aaai.v36i7.20695.
short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the
AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336.
date_created: 2023-02-05T17:29:50Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2023-11-30T10:55:37Z
day: '28'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v36i7.20695
ec_funded: 1
external_id:
arxiv:
- '2112.09495'
intvolume: ' 36'
issue: '7'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2112.09495
month: '06'
oa: 1
oa_version: Preprint
page: 7326-7336
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- '9781577358350'
issn:
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Stability verification in stochastic control systems via neural network supermartingales
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '14601'
abstract:
- lang: eng
text: "In this work, we address the problem of learning provably stable neural\r\nnetwork
policies for stochastic control systems. While recent work has\r\ndemonstrated
the feasibility of certifying given policies using martingale\r\ntheory, the problem
of how to learn such policies is little explored. Here, we\r\nstudy the effectiveness
of jointly learning a policy together with a martingale\r\ncertificate that proves
its stability using a single learning algorithm. We\r\nobserve that the joint
optimization problem becomes easily stuck in local\r\nminima when starting from
a randomly initialized policy. Our results suggest\r\nthat some form of pre-training
of the policy is required for the joint\r\noptimization to repair and verify the
policy successfully."
article_processing_charge: No
author:
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies
in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991
apa: Zikelic, D., Lechner, M., Chatterjee, K., & Henzinger, T. A. (n.d.). Learning
stabilizing policies in stochastic control systems. arXiv. https://doi.org/10.48550/arXiv.2205.11991
chicago: Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger.
“Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d.
https://doi.org/10.48550/arXiv.2205.11991.
ieee: D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing
policies in stochastic control systems,” arXiv. .
ista: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies
in stochastic control systems. arXiv, 10.48550/arXiv.2205.11991.
mla: Zikelic, Dorde, et al. “Learning Stabilizing Policies in Stochastic Control
Systems.” ArXiv, doi:10.48550/arXiv.2205.11991.
short: D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.).
date_created: 2023-11-24T13:22:30Z
date_published: 2022-05-24T00:00:00Z
date_updated: 2023-11-30T10:55:37Z
day: '24'
department:
- _id: KrCh
- _id: ToHe
doi: 10.48550/arXiv.2205.11991
ec_funded: 1
external_id:
arxiv:
- '2205.11991'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2205.11991
month: '05'
oa: 1
oa_version: Preprint
project:
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call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
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call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
status: public
title: Learning stabilizing policies in stochastic control systems
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2022'
...