Volume

Dagstuhl Seminar Proceedings, Volume 9371



Publication Details

  • published at: 2010-04-22
  • Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik

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Document
09371 Abstracts Collection – Algorithmic Methods for Distributed Cooperative Systems

Authors: Sándor Fekete, Stefan Fischer, Martin Riedmiller, and Suri Dubhash


Abstract
From 06.09.09 to 11.09.09 the Dagstuhl Seminar 09371 ``Algorithmic Methods for Distributed Cooperative Systems'' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. The purpose of this workshop was to bring together researchers from different disciplines whose central interest is in both algorithmic foundations and application scenarios of distributed cooperative systems. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.

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Sándor Fekete, Stefan Fischer, Martin Riedmiller, and Suri Dubhash. 09371 Abstracts Collection – Algorithmic Methods for Distributed Cooperative Systems. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{fekete_et_al:DagSemProc.09371.1,
  author =	{Fekete, S\'{a}ndor and Fischer, Stefan and Riedmiller, Martin and Dubhash, Suri},
  title =	{{09371 Abstracts Collection – Algorithmic Methods for Distributed Cooperative Systems}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--16},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.1},
  URN =		{urn:nbn:de:0030-drops-25224},
  doi =		{10.4230/DagSemProc.09371.1},
  annote =	{Keywords: Algorithms, cooperative systems, sensor networks, multi-robot systems, applications}
}
Document
Cooperative Multi-Agent Systems from the Reinforcement Learning Perspective – Challenges, Algorithms, and an Application

Authors: Thomas Gabel


Abstract
Reinforcement Learning has established as a framework that allows an autonomous agent for automatically acquiring – in a trial and error-based manner – a behavior policy based on a specification of the desired behavior of the system. In a multi-agent system, however, the decentralization of the control and observation of the system among independent agents has a significant impact on learning and it complexity. In this survey talk, we briefly review the foundations of single-agent reinforcement learning, point to the merits and challenges when applied in a multi-agent setting, and illustrate its potential in the context of an application from the field of manufacturing control and scheduling.

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Thomas Gabel. Cooperative Multi-Agent Systems from the Reinforcement Learning Perspective – Challenges, Algorithms, and an Application. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{gabel:DagSemProc.09371.2,
  author =	{Gabel, Thomas},
  title =	{{Cooperative Multi-Agent Systems from the Reinforcement Learning Perspective – Challenges, Algorithms, and an Application}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.2},
  URN =		{urn:nbn:de:0030-drops-24265},
  doi =		{10.4230/DagSemProc.09371.2},
  annote =	{Keywords: Multi-agent reinforcement learning, decentralized control, job-shop scheduling}
}
Document
Local Algorithms: Self-Stabilization on Speed

Authors: Christoph Lenzen, Jukka Suomela, and Roger Wattenhofer


Abstract
An introduction to distributed algorithms, in particular local algorithms. Essentially a practice talk of my SSS 2009 invited talk.

Cite as

Christoph Lenzen, Jukka Suomela, and Roger Wattenhofer. Local Algorithms: Self-Stabilization on Speed. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{lenzen_et_al:DagSemProc.09371.3,
  author =	{Lenzen, Christoph and Suomela, Jukka and Wattenhofer, Roger},
  title =	{{Local Algorithms: Self-Stabilization on Speed}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--18},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.3},
  URN =		{urn:nbn:de:0030-drops-24257},
  doi =		{10.4230/DagSemProc.09371.3},
  annote =	{Keywords: Local Algorithms, Self-Stabilization, Lower Bounds, Upper Bounds, MIS}
}
Document
On the Fairness of Probabilistic Schedulers for Population Protocols

Authors: Ioannis Chatzigiannakis, Shlomi Dolev, Sándor Fekete, Othon Michail, and Paul Spirakis


Abstract
We propose a novel, generic definition of emph{probabilistic schedulers} for population protocols. We design two new schedulers, the emph{State Scheduler} and the emph{Transition Function Scheduler}. Both possess the significant capability of being emph{protocol-aware}, i.e. they can assign transition probabilities based on information concerning the underlying protocol. We prove that the proposed schedulers, and also the emph{Random Scheduler} that was defined by Angluin et al. cite{AADFP04}, are all fair with probability $1$. We also define and study emph{equivalence} between schedulers w.r.t. emph{performance} and emph{correctness} and prove that there exist fair probabilistic schedulers that are not equivalent w.r.t. to performance and others that are not equivalent w.r.t. correctness. We implement our schedulers using a new tool for simulating population protocols and evaluate their performance from the viewpoint of experimental analysis and verification. We study three representative protocols to verify stability, and compare the experimental time to convergence with the known complexity bounds. We run our experiments from very small to extremely large populations (of up to $10^{8}$ agents). We get very promising results both of theoretical and practical interest.

Cite as

Ioannis Chatzigiannakis, Shlomi Dolev, Sándor Fekete, Othon Michail, and Paul Spirakis. On the Fairness of Probabilistic Schedulers for Population Protocols. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{chatzigiannakis_et_al:DagSemProc.09371.4,
  author =	{Chatzigiannakis, Ioannis and Dolev, Shlomi and Fekete, S\'{a}ndor and Michail, Othon and Spirakis, Paul},
  title =	{{On the Fairness of Probabilistic Schedulers for Population Protocols}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--23},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.4},
  URN =		{urn:nbn:de:0030-drops-24286},
  doi =		{10.4230/DagSemProc.09371.4},
  annote =	{Keywords: Population Protocols, Fairness, Probabilistic Schedulers, Communicating Automata, Sensor Networks, Experimental Evaluation}
}
Document
On the Fundamental Limits of Broadcasting in Wireless Mobile Networks

Authors: Giovanni Resta and Paolo Santi


Abstract
In this talk, we investigate the fundamental properties of broadcasting in mobile wireless networks. In particular, we characterize broadcast capacity and latency of a mobile network, subject to the condition that the stationary node spatial distribution generated by the mobility model is uniform. We first study the intrinsic properties of broadcasting, and present a broadcasting scheme, called RippleCast, that simultaneously achieves asymptotically optimal broadcast capacity and latency, subject to a weak upper bound on the maximum node velocity. This study intendedly ignores the burden related to the selection of broadcast relay nodes within the mobile network, and shows that optimal broadcasting in mobile networks is, in principle, possible. We then investigate the broadcasting problem when the relay selection burden is taken into account, and present a combined distributed leader election and broadcasting scheme achieving a broadcast capacity and latency which is within a $Theta((log n)^{1+frac{2}{alpha}})$ factor from optimal, where $n$ is the number of mobile nodes and $alpha>2$ is the path loss exponent. However, this result holds only under the assumption that the upper bound on node velocity converges to zero (although with a very slow, poly-logarithmic rate) as $n$ grows to infinity. To the best of our knowledge, our is the first paper investigating the effects of node mobility on the fundamental properties of broadcasting, and showing that, while optimal broadcasting in a mobile network is in principle possible, the coordination efforts related to the selection of broadcast relay nodes lead to sub-optimal broadcasting performance.

Cite as

Giovanni Resta and Paolo Santi. On the Fundamental Limits of Broadcasting in Wireless Mobile Networks. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{resta_et_al:DagSemProc.09371.5,
  author =	{Resta, Giovanni and Santi, Paolo},
  title =	{{On the Fundamental Limits of Broadcasting in Wireless Mobile Networks}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--9},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.5},
  URN =		{urn:nbn:de:0030-drops-24273},
  doi =		{10.4230/DagSemProc.09371.5},
  annote =	{Keywords: Wireless networks, mobile networks, broadcast capacity, broadcast latency, SINR interference model}
}
Document
Stabilizing Consensus with the Power of Two Choices

Authors: Benjamin Doerr, Leslie Ann Goldberg, Lorenz Minder, Thomas Sauerwald, and Christian Scheideler


Abstract
Consensus problems occur in many contexts and have therefore been intensively studied in the past. In the standard consensus problem there are n processes with possibly different input values and the goal is to eventually reach a point at which all processes commit to exactly one of these values. We are studying a slight variant of the consensus problem called the stabilizing consensus problem. In this problem, we do not require that each process commits to a final value at some point, but that eventually they arrive at a common value without necessarily being aware of that. This should work irrespective of the states in which the processes are starting. Coming up with a self-stabilizing rule is easy without adversarial involvement, but we allow some T-bounded adversary to manipulate any T processes at any time. In this situation, a perfect consensus is impossible to reach, so we only require that there is a time point t and value v so that at any point after t, all but up to O(T) processes agree on v, which we call an almost stable consensus. As we will demonstrate, there is a surprisingly simple rule for the standard message passing model that just needs O(log n loglog n) time for any sqrt{n}-bounded adversary and just O(log n) time without adversarial involvement, with high probability, to reach an (almost) stable consensus from any initial state. A stable consensus is reached, with high probability, in the absence of adversarial involvement.

Cite as

Benjamin Doerr, Leslie Ann Goldberg, Lorenz Minder, Thomas Sauerwald, and Christian Scheideler. Stabilizing Consensus with the Power of Two Choices. In Algorithmic Methods for Distributed Cooperative Systems. Dagstuhl Seminar Proceedings, Volume 9371, pp. 1-21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)


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@InProceedings{doerr_et_al:DagSemProc.09371.6,
  author =	{Doerr, Benjamin and Goldberg, Leslie Ann and Minder, Lorenz and Sauerwald, Thomas and Scheideler, Christian},
  title =	{{Stabilizing Consensus with the Power of Two Choices}},
  booktitle =	{Algorithmic Methods for Distributed Cooperative Systems},
  pages =	{1--21},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9371},
  editor =	{S\'{a}ndor Fekete and Stefan Fischer and Martin Riedmiller and Suri Subhash},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09371.6},
  URN =		{urn:nbn:de:0030-drops-24290},
  doi =		{10.4230/DagSemProc.09371.6},
  annote =	{Keywords: Distributed consensus}
}

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