---
_id: '45895'
author:
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
- first_name: Marten
full_name: Maack, Marten
id: '88252'
last_name: Maack
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
id: '15523'
last_name: Meyer auf der Heide
- first_name: Simon
full_name: Pukrop, Simon
id: '44428'
last_name: Pukrop
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
citation:
ama: 'Karl H, Maack M, Meyer auf der Heide F, Pukrop S, Redder A. On-The-Fly Compute
Centers II: Execution of Composed Services in Configurable Compute Centers. In:
Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly
Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe
des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:183-202.
doi:10.5281/zenodo.8068664'
apa: 'Karl, H., Maack, M., Meyer auf der Heide, F., Pukrop, S., & Redder, A.
(2023). On-The-Fly Compute Centers II: Execution of Composed Services in Configurable
Compute Centers. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth,
& H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services
in dynamic markets (Vol. 412, pp. 183–202). Heinz Nixdorf Institut, Universität
Paderborn. https://doi.org/10.5281/zenodo.8068664'
bibtex: '@inbook{Karl_Maack_Meyer auf der Heide_Pukrop_Redder_2023, place={Paderborn},
series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={On-The-Fly
Compute Centers II: Execution of Composed Services in Configurable Compute Centers},
volume={412}, DOI={10.5281/zenodo.8068664},
booktitle={On-The-Fly Computing -- Individualized IT-services in dynamic markets},
publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Karl, Holger
and Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon and Redder,
Adrian}, editor={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner,
Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, pages={183–202},
collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }'
chicago: 'Karl, Holger, Marten Maack, Friedhelm Meyer auf der Heide, Simon Pukrop,
and Adrian Redder. “On-The-Fly Compute Centers II: Execution of Composed Services
in Configurable Compute Centers.” In On-The-Fly Computing -- Individualized
IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer
auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:183–202.
Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut,
Universität Paderborn, 2023. https://doi.org/10.5281/zenodo.8068664.'
ieee: 'H. Karl, M. Maack, F. Meyer auf der Heide, S. Pukrop, and A. Redder, “On-The-Fly
Compute Centers II: Execution of Composed Services in Configurable Compute Centers,”
in On-The-Fly Computing -- Individualized IT-services in dynamic markets,
vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and
H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023,
pp. 183–202.'
mla: 'Karl, Holger, et al. “On-The-Fly Compute Centers II: Execution of Composed
Services in Configurable Compute Centers.” On-The-Fly Computing -- Individualized
IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol.
412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 183–202, doi:10.5281/zenodo.8068664.'
short: 'H. Karl, M. Maack, F. Meyer auf der Heide, S. Pukrop, A. Redder, in: C.-J.
Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.),
On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf
Institut, Universität Paderborn, Paderborn, 2023, pp. 183–202.'
date_created: 2023-07-07T08:24:28Z
date_updated: 2023-07-07T11:16:53Z
ddc:
- '004'
department:
- _id: '7'
doi: 10.5281/zenodo.8068664
editor:
- first_name: Claus-Jochen
full_name: Haake, Claus-Jochen
last_name: Haake
- first_name: Friedhelm
full_name: Meyer auf der Heide, Friedhelm
last_name: Meyer auf der Heide
- first_name: Marco
full_name: Platzner, Marco
last_name: Platzner
- first_name: Henning
full_name: Wachsmuth, Henning
last_name: Wachsmuth
- first_name: Heike
full_name: Wehrheim, Heike
last_name: Wehrheim
file:
- access_level: open_access
content_type: application/pdf
creator: florida
date_created: 2023-07-07T08:24:20Z
date_updated: 2023-07-07T11:16:52Z
file_id: '45896'
file_name: C4-Chapter-SFB-Buch-Final.pdf
file_size: 1803186
relation: main_file
file_date_updated: 2023-07-07T11:16:52Z
has_accepted_license: '1'
intvolume: ' 412'
language:
- iso: eng
oa: '1'
page: 183-202
place: Paderborn
project:
- _id: '1'
grant_number: '160364472'
name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen
in dynamischen Märkten '
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
- _id: '16'
grant_number: '160364472'
name: 'SFB 901 - C4: SFB 901 - On-The-Fly Compute Centers II: Ausführung komponierter
Dienste in konfigurierbaren Rechenzentren (Subproject C4)'
publication: On-The-Fly Computing -- Individualized IT-services in dynamic markets
publisher: Heinz Nixdorf Institut, Universität Paderborn
series_title: Verlagsschriftenreihe des Heinz Nixdorf Instituts
status: public
title: 'On-The-Fly Compute Centers II: Execution of Composed Services in Configurable
Compute Centers'
type: book_chapter
user_id: '477'
volume: 412
year: '2023'
...
---
_id: '32811'
abstract:
- lang: eng
text: 'The decentralized nature of multi-agent systems requires continuous data
exchange to achieve global objectives. In such scenarios, Age of Information (AoI)
has become an important metric of the freshness of exchanged data due to the error-proneness
and delays of communication systems. Communication systems usually possess dependencies:
the process describing the success or failure of communication is highly correlated
when these attempts are ``close'''' in some domain (e.g. in time, frequency, space
or code as in wireless communication) and is, in general, non-stationary. To study
AoI in such scenarios, we consider an abstract event-based AoI process $\Delta(n)$,
expressing time since the last update: If, at time $n$, a monitoring node receives
a status update from a source node (event $A(n-1)$ occurs), then $\Delta(n)$ is
reset to one; otherwise, $\Delta(n)$ grows linearly in time. This AoI process
can thus be viewed as a special random walk with resets. The event process $A(n)$
may be nonstationary and we merely assume that its temporal dependencies decay
sufficiently, described by $\alpha$-mixing. We calculate moment bounds for the
resulting AoI process as a function of the mixing rate of $A(n)$. Furthermore,
we prove that the AoI process $\Delta(n)$ is itself $\alpha$-mixing from which
we conclude a strong law of large numbers for $\Delta(n)$. These results are new,
since AoI processes have not been studied so far in this general strongly mixing
setting. This opens up future work on renewal processes with non-independent interarrival
times.'
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Redder A, Ramaswamy A, Karl H. Age of Information Process under Strongly Mixing
Communication -- Moment Bound, Mixing Rate and Strong Law. In: Proceedings
of the 58th Allerton Conference on Communication, Control, and Computing.
; 2022.'
apa: Redder, A., Ramaswamy, A., & Karl, H. (2022). Age of Information Process
under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law.
Proceedings of the 58th Allerton Conference on Communication, Control, and
Computing. 58th Allerton Conference on Communication, Control, and Computing.
bibtex: '@inproceedings{Redder_Ramaswamy_Karl_2022, title={Age of Information Process
under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong Law},
booktitle={Proceedings of the 58th Allerton Conference on Communication, Control,
and Computing}, author={Redder, Adrian and Ramaswamy, Arunselvan and Karl, Holger},
year={2022} }'
chicago: Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Age of Information
Process under Strongly Mixing Communication -- Moment Bound, Mixing Rate and Strong
Law.” In Proceedings of the 58th Allerton Conference on Communication, Control,
and Computing, 2022.
ieee: A. Redder, A. Ramaswamy, and H. Karl, “Age of Information Process under Strongly
Mixing Communication -- Moment Bound, Mixing Rate and Strong Law,” presented at
the 58th Allerton Conference on Communication, Control, and Computing, 2022.
mla: Redder, Adrian, et al. “Age of Information Process under Strongly Mixing Communication
-- Moment Bound, Mixing Rate and Strong Law.” Proceedings of the 58th Allerton
Conference on Communication, Control, and Computing, 2022.
short: 'A. Redder, A. Ramaswamy, H. Karl, in: Proceedings of the 58th Allerton Conference
on Communication, Control, and Computing, 2022.'
conference:
name: 58th Allerton Conference on Communication, Control, and Computing
date_created: 2022-08-15T09:59:17Z
date_updated: 2022-11-18T09:31:19Z
ddc:
- '000'
department:
- _id: '75'
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
publication: Proceedings of the 58th Allerton Conference on Communication, Control,
and Computing
status: public
title: Age of Information Process under Strongly Mixing Communication -- Moment Bound,
Mixing Rate and Strong Law
type: conference
user_id: '477'
year: '2022'
...
---
_id: '30793'
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: 'Redder A, Ramaswamy A, Karl H. Multi-agent Policy Gradient Algorithms for
Cyber-physical Systems with Lossy Communication. In: Proceedings of the 14th
International Conference on Agents and Artificial Intelligence. SCITEPRESS
- Science and Technology Publications; 2022. doi:10.5220/0010845400003116'
apa: Redder, A., Ramaswamy, A., & Karl, H. (2022). Multi-agent Policy Gradient
Algorithms for Cyber-physical Systems with Lossy Communication. Proceedings
of the 14th International Conference on Agents and Artificial Intelligence.
https://doi.org/10.5220/0010845400003116
bibtex: '@inproceedings{Redder_Ramaswamy_Karl_2022, title={Multi-agent Policy Gradient
Algorithms for Cyber-physical Systems with Lossy Communication}, DOI={10.5220/0010845400003116},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial
Intelligence}, publisher={SCITEPRESS - Science and Technology Publications}, author={Redder,
Adrian and Ramaswamy, Arunselvan and Karl, Holger}, year={2022} }'
chicago: Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Multi-Agent Policy
Gradient Algorithms for Cyber-Physical Systems with Lossy Communication.” In Proceedings
of the 14th International Conference on Agents and Artificial Intelligence.
SCITEPRESS - Science and Technology Publications, 2022. https://doi.org/10.5220/0010845400003116.
ieee: 'A. Redder, A. Ramaswamy, and H. Karl, “Multi-agent Policy Gradient Algorithms
for Cyber-physical Systems with Lossy Communication,” 2022, doi: 10.5220/0010845400003116.'
mla: Redder, Adrian, et al. “Multi-Agent Policy Gradient Algorithms for Cyber-Physical
Systems with Lossy Communication.” Proceedings of the 14th International Conference
on Agents and Artificial Intelligence, SCITEPRESS - Science and Technology
Publications, 2022, doi:10.5220/0010845400003116.
short: 'A. Redder, A. Ramaswamy, H. Karl, in: Proceedings of the 14th International
Conference on Agents and Artificial Intelligence, SCITEPRESS - Science and Technology
Publications, 2022.'
date_created: 2022-04-06T07:18:36Z
date_updated: 2022-11-18T09:32:14Z
ddc:
- '006'
department:
- _id: '75'
doi: 10.5220/0010845400003116
file:
- access_level: closed
content_type: application/pdf
creator: aredder
date_created: 2022-08-31T07:10:13Z
date_updated: 2022-08-31T07:10:13Z
file_id: '33237'
file_name: ICCART2022.pdf
file_size: 298926
relation: main_file
success: 1
file_date_updated: 2022-08-31T07:10:13Z
has_accepted_license: '1'
language:
- iso: eng
project:
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
- _id: '24'
name: 'NICCI-CN: Netzgewahre Regelung & regelungsgewahre Netze'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
publication: Proceedings of the 14th International Conference on Agents and Artificial
Intelligence
publication_status: published
publisher: SCITEPRESS - Science and Technology Publications
status: public
title: Multi-agent Policy Gradient Algorithms for Cyber-physical Systems with Lossy
Communication
type: conference
user_id: '477'
year: '2022'
...
---
_id: '30790'
abstract:
- lang: eng
text: "Iterative distributed optimization algorithms involve multiple agents that\r\ncommunicate
with each other, over time, in order to minimize/maximize a global\r\nobjective.
In the presence of unreliable communication networks, the\r\nAge-of-Information
(AoI), which measures the freshness of data received, may be\r\nlarge and hence
hinder algorithmic convergence. In this paper, we study the\r\nconvergence of
general distributed gradient-based optimization algorithms in\r\nthe presence
of communication that neither happens periodically nor at\r\nstochastically independent
points in time. We show that convergence is\r\nguaranteed provided the random
variables associated with the AoI processes are\r\nstochastically dominated by
a random variable with finite first moment. This\r\nimproves on previous requirements
of boundedness of more than the first moment.\r\nWe then introduce stochastically
strongly connected (SSC) networks, a new\r\nstochastic form of strong connectedness
for time-varying networks. We show: If\r\nfor any $p \\ge0$ the processes that
describe the success of communication\r\nbetween agents in a SSC network are $\\alpha$-mixing
with $n^{p-1}\\alpha(n)$\r\nsummable, then the associated AoI processes are stochastically
dominated by a\r\nrandom variable with finite $p$-th moment. In combination with
our first\r\ncontribution, this implies that distributed stochastic gradient descend\r\nconverges
in the presence of AoI, if $\\alpha(n)$ is summable."
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: Redder A, Ramaswamy A, Karl H. Distributed gradient-based optimization in the
presence of dependent aperiodic communication. arXiv:220111343. Published
online 2022.
apa: Redder, A., Ramaswamy, A., & Karl, H. (2022). Distributed gradient-based
optimization in the presence of dependent aperiodic communication. In arXiv:2201.11343.
bibtex: '@article{Redder_Ramaswamy_Karl_2022, title={Distributed gradient-based
optimization in the presence of dependent aperiodic communication}, journal={arXiv:2201.11343},
author={Redder, Adrian and Ramaswamy, Arunselvan and Karl, Holger}, year={2022}
}'
chicago: Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Distributed Gradient-Based
Optimization in the Presence of Dependent Aperiodic Communication.” ArXiv:2201.11343,
2022.
ieee: A. Redder, A. Ramaswamy, and H. Karl, “Distributed gradient-based optimization
in the presence of dependent aperiodic communication,” arXiv:2201.11343.
2022.
mla: Redder, Adrian, et al. “Distributed Gradient-Based Optimization in the Presence
of Dependent Aperiodic Communication.” ArXiv:2201.11343, 2022.
short: A. Redder, A. Ramaswamy, H. Karl, ArXiv:2201.11343 (2022).
date_created: 2022-04-06T06:53:38Z
date_updated: 2022-11-18T09:33:01Z
department:
- _id: '75'
external_id:
arxiv:
- '2201.11343'
language:
- iso: eng
project:
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
publication: arXiv:2201.11343
status: public
title: Distributed gradient-based optimization in the presence of dependent aperiodic
communication
type: preprint
user_id: '477'
year: '2022'
...
---
_id: '30791'
abstract:
- lang: eng
text: "We present sufficient conditions that ensure convergence of the multi-agent\r\nDeep
Deterministic Policy Gradient (DDPG) algorithm. It is an example of one of\r\nthe
most popular paradigms of Deep Reinforcement Learning (DeepRL) for tackling\r\ncontinuous
action spaces: the actor-critic paradigm. In the setting considered\r\nherein,
each agent observes a part of the global state space in order to take\r\nlocal
actions, for which it receives local rewards. For every agent, DDPG\r\ntrains
a local actor (policy) and a local critic (Q-function). The analysis\r\nshows
that multi-agent DDPG using neural networks to approximate the local\r\npolicies
and critics converge to limits with the following properties: The\r\ncritic limits
minimize the average squared Bellman loss; the actor limits\r\nparameterize a
policy that maximizes the local critic's approximation of\r\n$Q_i^*$, where $i$
is the agent index. The averaging is with respect to a\r\nprobability distribution
over the global state-action space. It captures the\r\nasymptotics of all local
training processes. Finally, we extend the analysis to\r\na fully decentralized
setting where agents communicate over a wireless network\r\nprone to delays and
losses; a typical scenario in, e.g., robotic applications."
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: Redder A, Ramaswamy A, Karl H. Asymptotic Convergence of Deep Multi-Agent Actor-Critic
Algorithms. arXiv:220100570. Published online 2022.
apa: Redder, A., Ramaswamy, A., & Karl, H. (2022). Asymptotic Convergence of
Deep Multi-Agent Actor-Critic Algorithms. In arXiv:2201.00570.
bibtex: '@article{Redder_Ramaswamy_Karl_2022, title={Asymptotic Convergence of Deep
Multi-Agent Actor-Critic Algorithms}, journal={arXiv:2201.00570}, author={Redder,
Adrian and Ramaswamy, Arunselvan and Karl, Holger}, year={2022} }'
chicago: Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Asymptotic Convergence
of Deep Multi-Agent Actor-Critic Algorithms.” ArXiv:2201.00570, 2022.
ieee: A. Redder, A. Ramaswamy, and H. Karl, “Asymptotic Convergence of Deep Multi-Agent
Actor-Critic Algorithms,” arXiv:2201.00570. 2022.
mla: Redder, Adrian, et al. “Asymptotic Convergence of Deep Multi-Agent Actor-Critic
Algorithms.” ArXiv:2201.00570, 2022.
short: A. Redder, A. Ramaswamy, H. Karl, ArXiv:2201.00570 (2022).
date_created: 2022-04-06T06:53:52Z
date_updated: 2022-11-18T09:33:42Z
department:
- _id: '75'
external_id:
arxiv:
- '2201.00570'
language:
- iso: eng
project:
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
publication: arXiv:2201.00570
status: public
title: Asymptotic Convergence of Deep Multi-Agent Actor-Critic Algorithms
type: preprint
user_id: '477'
year: '2022'
...
---
_id: '32854'
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Holger
full_name: Karl, Holger
id: '126'
last_name: Karl
citation:
ama: Redder A, Ramaswamy A, Karl H. Practical Network Conditions for the Convergence
of Distributed Optimization. IFAC-PapersOnLine. 2022;55(13):133–138.
apa: Redder, A., Ramaswamy, A., & Karl, H. (2022). Practical Network Conditions
for the Convergence of Distributed Optimization. IFAC-PapersOnLine, 55(13),
133–138.
bibtex: '@article{Redder_Ramaswamy_Karl_2022, title={Practical Network Conditions
for the Convergence of Distributed Optimization}, volume={55}, number={13}, journal={IFAC-PapersOnLine},
publisher={Elsevier}, author={Redder, Adrian and Ramaswamy, Arunselvan and Karl,
Holger}, year={2022}, pages={133–138} }'
chicago: 'Redder, Adrian, Arunselvan Ramaswamy, and Holger Karl. “Practical Network
Conditions for the Convergence of Distributed Optimization.” IFAC-PapersOnLine
55, no. 13 (2022): 133–138.'
ieee: A. Redder, A. Ramaswamy, and H. Karl, “Practical Network Conditions for the
Convergence of Distributed Optimization,” IFAC-PapersOnLine, vol. 55, no.
13, pp. 133–138, 2022.
mla: Redder, Adrian, et al. “Practical Network Conditions for the Convergence of
Distributed Optimization.” IFAC-PapersOnLine, vol. 55, no. 13, Elsevier,
2022, pp. 133–138.
short: A. Redder, A. Ramaswamy, H. Karl, IFAC-PapersOnLine 55 (2022) 133–138.
conference:
name: IFAC Conference on Networked Systems
date_created: 2022-08-16T09:12:55Z
date_updated: 2022-11-18T10:05:14Z
ddc:
- '006'
department:
- _id: '75'
file:
- access_level: closed
content_type: application/pdf
creator: aredder
date_created: 2022-08-31T07:06:30Z
date_updated: 2022-08-31T07:06:30Z
file_id: '33236'
file_name: NecSys2022____Practical_Conditions_for_Conv.pdf
file_size: 298395
relation: main_file
success: 1
file_date_updated: 2022-08-31T07:06:30Z
has_accepted_license: '1'
intvolume: ' 55'
issue: '13'
language:
- iso: eng
page: 133–138
project:
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
publication: IFAC-PapersOnLine
publisher: Elsevier
status: public
title: Practical Network Conditions for the Convergence of Distributed Optimization
type: journal_article
user_id: '477'
volume: 55
year: '2022'
...
---
_id: '24140'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Daniel E.
full_name: Quevedo, Daniel E.
last_name: Quevedo
citation:
ama: Ramaswamy A, Redder A, Quevedo DE. Distributed optimization over time-varying
networks with stochastic information delays. IEEE Transactions on Automatic
Control. Published online 2021:1-1. doi:10.1109/TAC.2021.3108492
apa: Ramaswamy, A., Redder, A., & Quevedo, D. E. (2021). Distributed optimization
over time-varying networks with stochastic information delays. IEEE Transactions
on Automatic Control, 1–1. https://doi.org/10.1109/TAC.2021.3108492
bibtex: '@article{Ramaswamy_Redder_Quevedo_2021, title={Distributed optimization
over time-varying networks with stochastic information delays}, DOI={10.1109/TAC.2021.3108492},
journal={IEEE Transactions on Automatic Control}, author={Ramaswamy, Arunselvan
and Redder, Adrian and Quevedo, Daniel E.}, year={2021}, pages={1–1} }'
chicago: Ramaswamy, Arunselvan, Adrian Redder, and Daniel E. Quevedo. “Distributed
Optimization over Time-Varying Networks with Stochastic Information Delays.” IEEE
Transactions on Automatic Control, 2021, 1–1. https://doi.org/10.1109/TAC.2021.3108492.
ieee: 'A. Ramaswamy, A. Redder, and D. E. Quevedo, “Distributed optimization over
time-varying networks with stochastic information delays,” IEEE Transactions
on Automatic Control, pp. 1–1, 2021, doi: 10.1109/TAC.2021.3108492.'
mla: Ramaswamy, Arunselvan, et al. “Distributed Optimization over Time-Varying Networks
with Stochastic Information Delays.” IEEE Transactions on Automatic Control,
2021, pp. 1–1, doi:10.1109/TAC.2021.3108492.
short: A. Ramaswamy, A. Redder, D.E. Quevedo, IEEE Transactions on Automatic Control
(2021) 1–1.
date_created: 2021-09-10T09:48:55Z
date_updated: 2022-08-16T09:16:43Z
doi: 10.1109/TAC.2021.3108492
language:
- iso: eng
page: 1-1
project:
- _id: '24'
name: 'NICCI-CN: Netzgewahre Regelung & regelungsgewahre Netze'
publication: IEEE Transactions on Automatic Control
status: public
title: Distributed optimization over time-varying networks with stochastic information
delays
type: journal_article
user_id: '52265'
year: '2021'
...
---
_id: '13443'
abstract:
- lang: eng
text: "This work considers the problem of control and resource allocation in networked\r\nsystems.
To this end, we present DIRA a Deep reinforcement learning based Iterative Resource\r\nAllocation
algorithm, which is scalable and control-aware. Our algorithm is tailored towards\r\nlarge-scale
problems where control and scheduling need to act jointly to optimize performance.\r\nDIRA
can be used to schedule general time-domain optimization based controllers. In
the present\r\nwork, we focus on control designs based on suitably adapted linear
quadratic regulators. We\r\napply our algorithm to networked systems with correlated
fading communication channels. Our\r\nsimulations show that DIRA scales well to
large scheduling problems."
author:
- first_name: Adrian
full_name: Redder, Adrian
id: '52265'
last_name: Redder
orcid: https://orcid.org/0000-0001-7391-4688
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Daniel
full_name: Quevedo, Daniel
last_name: Quevedo
citation:
ama: 'Redder A, Ramaswamy A, Quevedo D. Deep reinforcement learning for scheduling
in large-scale networked control systems. In: Proceedings of the 8th IFAC Workshop
on Distributed Estimation and Control in Networked Systems. ; 2019.'
apa: Redder, A., Ramaswamy, A., & Quevedo, D. (2019). Deep reinforcement learning
for scheduling in large-scale networked control systems. In Proceedings of
the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems.
Chicago, USA.
bibtex: '@inproceedings{Redder_Ramaswamy_Quevedo_2019, title={Deep reinforcement
learning for scheduling in large-scale networked control systems}, booktitle={Proceedings
of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems},
author={Redder, Adrian and Ramaswamy, Arunselvan and Quevedo, Daniel}, year={2019}
}'
chicago: Redder, Adrian, Arunselvan Ramaswamy, and Daniel Quevedo. “Deep Reinforcement
Learning for Scheduling in Large-Scale Networked Control Systems.” In Proceedings
of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems,
2019.
ieee: A. Redder, A. Ramaswamy, and D. Quevedo, “Deep reinforcement learning for
scheduling in large-scale networked control systems,” in Proceedings of the
8th IFAC Workshop on Distributed Estimation and Control in Networked Systems,
Chicago, USA, 2019.
mla: Redder, Adrian, et al. “Deep Reinforcement Learning for Scheduling in Large-Scale
Networked Control Systems.” Proceedings of the 8th IFAC Workshop on Distributed
Estimation and Control in Networked Systems, 2019.
short: 'A. Redder, A. Ramaswamy, D. Quevedo, in: Proceedings of the 8th IFAC Workshop
on Distributed Estimation and Control in Networked Systems, 2019.'
conference:
end_date: 2019-09-17
location: Chicago, USA
name: 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems
- NECSYS 2019
start_date: 2019-09-16
date_created: 2019-09-23T16:00:58Z
date_updated: 2022-01-06T06:51:36Z
ddc:
- '620'
file:
- access_level: local
content_type: application/pdf
creator: aredder
date_created: 2019-09-23T15:48:33Z
date_updated: 2019-09-23T16:21:16Z
file_id: '13444'
file_name: ifacconf.pdf
file_size: 371429
relation: main_file
file_date_updated: 2019-09-23T16:21:16Z
has_accepted_license: '1'
keyword:
- Networked control systems
- deep reinforcement learning
- large-scale systems
- resource scheduling
- stochastic control
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1905.05992
oa: '1'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control
in Networked Systems
publication_status: published
status: public
title: Deep reinforcement learning for scheduling in large-scale networked control
systems
type: conference
user_id: '52265'
year: '2019'
...