Why is it important to get cited?

♫ "Hey! I just met you, and this is crazy,
      but here's my paper, so cite me, maybe?" ♫

(to be sung to the tune of "Call me maybe" by Carly Rae Jepsen, idea for text adaptation by Nikolaj Marchenko)

If this would work, you would find a lot of people singing that tune at conferences. The reason why it is important to get cited is because the number of citations of your publications have become an assessment of your scientific performance. The most famous indicator is the h-index [1], stating the largest number h for which there are at least h papers with at least h citations each.

20 years ago, a scientist was assessed by the number of papers she or he managed to write and publish. Getting a paper published was difficult, because there was limited space in the journals and each issue was a costly and time-consuming endeavor including typesetting, printing, distribution. In economic terms this means we had a shortage of a resource which made it valuable.

Today, things are better with regard to cost and effort for a publication - typsetting software is fast and easy to use and costs are lower than in the past. And when the Internet became the main medium instead of paper, printing costs vanished. If you like, you can found a new journal by just investing some time into the setup of a webpage template. Except from your own work time, personal costs would be no issue, since traditionally, being a journal's editor or reviewer is considered an honorary but unpaid job. This issues a quality assurance problem: If everybody can publish by themselves or provide an easy publication opportunity for others, the number of publications lose their status as a criterion for scientific quality and success. Therefore, attention has shifted to measure the actual impact of a publication in order to infer about its quality. The easy formula is: the more other works are influenced by a publication, the better this publication/work must have been.

This concept has its pros and cons. On the positive side, for at least all publications on the internet, the number of citations can be calculated automatically - Google scholar does it for you. Second, there is a good correlation between successful scientists and their number of citations. Negative aspects are that citations from publications which are not online are usually not included. There is also a bias depending on the scientific field, although there is work suggesting correction factors for this bias. The method further counts citations without distinction of the quality of the citation (be it positive, negative, long, brief, etc.) And finally, counting citations primarily measures the popularity of a paper, which explains why successful (popular) scientists have lots of citations. Still it appears that counting citations is currently the best way to assess publications with low effort. And it is a nice application of network theory.

Citations can be also used to assess journals. The more the publications in a journal are cited by others, the better is the journal. If everybody tries to get their papers published in journals with high impact, i.e. many citations, the competition leads to situation with a shortage on excellent publication places. Interesting is that a top journal does not require more effort than one with lower impact. The self-organizing effect of authors competing for the 'best' journals puts these journals in the convenient situation that they can pick the best papers - which in turn helps them in keeping their position. Regardless of the flaws of the citation-based impact analysis, as long as it is used by so many people, you have to play along.

Finally, some tips you might have been waiting for:
How can you push your h-index by maximizing the chance to get cited?

• Make your publications available online (mine are here btw)
• Discuss your work with others
• Write good papers. Interesting comprehensive work is more likely to be cited.
• Avoid low-impact journals and conferences
• Publish in the language which is most common for your field of research. In most cases this is english. 
• Add your paper as reference to appropriate pages in social networks (e.g., Wikipedia)

Note that these tips in general are part of serious research work. They make sense either you believe in the h-index or not. Don't try to fake you h-index, e.g. by massively citing yourself. Self-citations are likely to be excluded in future h-index calculations. Technically, excluding self-citations will be easy to implement by Google Scholar and co.

Links

1. h-index. Wikipedia
2. Google Scholar citation count (took myself as example)
3. J. E. Iglesias and C. Pecharromán. Scaling the h-index for different scientific ISI fields. Scientometrics, Vol. 73, No. 3 (2007)
4. W. Elmenreich. Google Scholar, Citation Indices, and the University of Klagenfurt. TEWI-Blog. November 2011

Call for Papers for the 7th International Workshop on Self-organizing Systems (IWSOS 2013)

Palma de Mallorca, Spain
May 9-10, 2013

http://ifisc.uib-csic.es/iwsos2013/

Extended Paper Submission Deadline: January 18, 2013

See you in Palma de Mallorca!
(Photo: Rafael Ortega Díaz/Wikipedia)

Scope

The main themes of IWSOS 2013 are from the fields of techno-social systems and networks-of-networks with their unique and complex blend of cognitive, social, and technological aspects. We will analyse how these systems self-organize, acquire their structure, and evolve. Thus, we aim to advance our understanding of such key infrastructures in our societies and, more generally, of these sorts of self-organizational processes in nature.

We are further interested in learning how to engineer such self-organizing networked systems to have desirable properties including dependability, predictability, and resilience in the face of the inevitable challenges that they face.

Building on the success of its predecessors, this multi-disciplinary workshop aims at bringing together leading international researchers from complex systems, distributed systems, and communication networks to create a visionary forum for discussing the future of self-organization in networked systems. We invite the submission of manuscripts that present original research results on the themes of self-organization in techno-social systems and networks-of-networks.

Key Topics

The workshop scope includes, but is not limited to, the following topical areas of self-organizing systems:

- Design and analysis of self-organizing and self-managing systems
- Inspiring models of self-organization in nature and society
- Structure, characteristics, and dynamics of self-organizing networks
- Self-organization in techno-social systems
- Self-organized social computation
- Self-organized communication systems
- Citizen Science
- Techniques and tools for modeling self-organizing systems
- Tools to quantify self-organization
- Control and control parameters of self-organizing systems
- Phase transitions in self-organizing systems
- Robustness and adaptation in self-organizing systems
- Self-organization in complex networks such as peer-to-peer, sensor,
  ad-hoc, vehicular, and social networks
- Self-organization in socio-economic systems
- User and operator-related aspects of man-made self-organizing systems
- Self-organizing multi-service networks and multi-network services
- Methods for configuration and management of large, complex networks
- Self-protection, self-configuration, diagnosis, and healing
- Self-organizing group and pattern formation
- Self-organizing mechanisms for task allocation, coordination and
  resource allocation
- Self-organizing information dissemination and content search
- Security and safety in self-organizing networked systems
- Risks and limits of self-organization
- The human in the loop of self-organizing networks
- Social, cognitive, and semantic aspects of self-organization
- Evolutionary principles of the (future, emerging) Internet
- Decentralized power management in the smart grid

Important Dates

Submission deadline: January 18, 2013 (extended)
Notification of acceptance: January 15, 2013
Camera-ready papers due: February 3, 2013
Conference dates: May 9-10, 2013

Papers

IWSOS 2013 invites the submission of manuscripts that present original research results which have not been previously published and are not currently under review by another conference or journal. Any previous or simultaneous publication of related material should be explicitly noted in the submission. All papers must be submitted in PDF format. Submissions will be peer reviewed by at least three members of the international technical program committee and judged on originality, significance, clarity, relevance, and correctness.

The Springer “LNCS Proceedings” style should be used for submission. Templates for LaTeX and Word are available at http://tiny.cc/qiohy.

Full papers should describe original research results. Submissions should be full-length papers up to 12 pages using the LNCS style (including figures, references, and a short abstract).

Short Papers should be position papers, challenging papers, and papers presenting first results. Short papers are up to 6 pages using the LNCS style (including figures, references, and a short abstract).

Proceedings

The proceedings will be published by Springer-Verlag in their Lecture Notes in Computer Science (LNCS) series. At least one of the authors of each accepted paper must attend IWSOS 2013 to present the paper.

Committees

General Chairs
Maxi San Miguel, IFISC (CSIC-University Balearic Islands), Spain
Hermann de Meer, University of Passau, Germany

Program Chairs
Falko Dressler, University of Innsbruck, Austria
Vittorio Loreto, Sapienza University of Rome, Italy

Publicity Chairs
Karin Anna Hummel, ETH Zurich, Switzerland
Carlos Gershenson, Universidad Nacional Autónoma de México, Mexico

Publication Chair
Wilfried Elmenreich, University of Passau, Germany

Local Organization Chair
Pere Colet, IFISC (CSIC-University Balearic Islands), Spain

Steering Committee
Hermann de Meer, Univ. Passau, Germany
David Hutchison, Lancaster University, UK
Bernhard Plattner, ETH Zurich, Switzerland
James Sterbenz, University of Kansas, USA
Randy Katz, UC Berkeley, USA
Georg Carle, TU Munich, Germany (IFIP TC6 Representative)
Karin Anna Hummel, ETH Zurich, Switzerland
Shlomo Havlin, Bar-Ilan University, Israel

Technical Program Committee
Karl Aberer, EPFL
Andrea Baronchelli, Northeastern University
Alain Barrat, Centre de Physique Theorique
Marc Barthelemy, Institut de Physique Théorique
Christian Bettstetter, University of Klagenfurt
Raffaele Bruno, Consiglio Nazionale delle Ricerche (CNR)
Claudio Castellano, CNR-ISC Rome
Ciro Cattuto, ISI Foundation Turin
Albert Diaz-Guilera, Universitat de Barcelona
Alois Ferscha, Johannes Kepler University Linz
Andreas Fischer, University of Passau
Santo Fortunato, Aalto University
Carlos Gershenson, Universidad Nacional Autónoma de México
Salima Hassas, University of Lyon 1
Boudewijn Haverkort, University of Twente
Poul Heegaard, Norwegian University of Science and Technology
Tom Holvoet, Katholieke Universiteit Leuven
Karin Anna Hummel, ETH Zurich
Sebastian Lehnhoff, OFFIS Institute for Information Technology
Hein Meling, University of Stavanger
Mirco Musolesi, University of Birmingham
Dimitri Papadimitriou, Alcatel-Lucent Bell
Christian Prehofer, Fraunhofer ESK
Jose Ramasco, Inst. for Cross-Disciplinary Physics and Complex Systems
Andreas Riener, Johannes Kepler University Linz
Kave Salamatian, Universite De Savoie
Hiroki Sayama, Binghamton University
Paul Smith, Austrian Institute of Technology
Bosiljka Tadic, Jozef Stefan Institute
Dirk Trossen, University of Cambridge

The 6-minute introduction to FREVO

Evolution is a slow process. In earth history, evolution took millions of years to achieve something. Computer simulations of evolutionary processes are much better, but still taking weeks of simulation time on a cluster to run some evolutionary algorithm.

We challenge this!

Our software FREVO (FRamework for EVOlutionary design) is aimed to reduce the time to implement, set up and run an evolutionary algorithm to evolve an agent's behavior as a solution to a particular control problem. FREVO is decomposing the task into problem definition, solution representation and the optimization method, in order to ... let's stop talking! I will show you in just 6 minutes!

As demonstrated in the video below, 6 minutes are sufficient to download the framework, install it, set up a simulation, evolve a neural network controller for an inverted pendulum problem and check the results! See for yourself!



The tool is available at http://frevo.sourceforge.com
There are also tutorials on advanced projects with FREVO. If you are doing research in engineering complex systems, this tool might be useful for your thesis ;-)

If FREVO is useful for you, please cite this paper:

A. Sobe, I. Fehérvári, and W. Elmenreich. Frevo: A tool for evolving and evaluating self-organizing systems. In Proceedings of the 1st International Workshop on Evaluation for Self-Adaptive and Self-Organizing Systems, Lyon, France, September 2012.

Symposium on Self-* Systems – Biological Foundations and Technological Applications

The Symposium on Self-* Systems – Biological Foundations and Technological Applications was part of the European Meeting on Cybernetics and Systems Research (EMCSR 2012) taking place from April 10-13 in Vienna, Austria. It was organized by Vesna Sesum-Cavic, Carlos Gershenson and Wilfried Elmenreich.

Tomonori Hasegawa presented insights on the self-referential logic of self-reproduction originally formulated by John von Neumann and introduced an implementation of this abstract architecture embedded within the Avida world [1]. In the experiments, a sophisticated von Neumann Self-Referential Machine, which was introduced as seeding mechanism, can degrade to a mere copy machine that has dropped the self-referential part. Thus, with this particular implementation, in this particular world, the von Neumann architecture proves to be evolutionarily unstable and degenerates, surprisingly easily, to a primitive, non-self-referential, “copying” or “template replication”, mode of reproduction
Questions arose if a von Neumann Self-Referential Machine could evolve from a simple self-copy machine in a different set-up. The von Neumann model has the advantage of enabling new and more ways to change the system upon mutation - but what could be the evolutionary pressure to have a von Neumann architecture evolved in the first place?
Current experiments did not include sexual reproduction - could that facilitate the evolution of more complex architectures?
More from the group can be found at http://evosym.rince.ie/

Modern software systems suffer from increased complexity. Large software systems are composed of many components that are interlinked. The internal states of these systems contain a huge amount of information. The main obstacles lie in the lack of the reliability and robustness which lead to poor performance. For complex intractable problems, a random search (Monte-Carlo method) does not perform well. New and advanced approaches are necessary to deal with complexity.
Milan Tuba proposed a guided Monte-Carlo search method based on a hybrid of reinforcement learning and a genetic algorithm[2]. As a proof-of-concept the approach is applied to the problem of information retrieval in the internet.
In the discussion, the performance of the algorithm in comparison to commercial search providers, like Google, was discussed.

Sander van Splunter presented ideas on the coordination and self-organization in crisis management[3]. The main idea is to move from a task-oriented top down approach towards an emergence-oriented bottom-up approach, while keeping, a hierarchical structure. However, higher level entities control lower levels by policy, not directly. Policy defines interaction, prioritization and coordination of entities.
An entity works as an independent agent following the given policies. An important feature could be the ability to predict the failure in a given subsystem.
According to EMCSR'12 keynote lecture of Peter Csermely we have to watch signs like slower recovery, increased self-similarity, and increased variance of fluctuation patterns in order to predict a system change into a state where it cannot handle the its environment with its current policies.
In the proposed crisis management of van Splunter and van Veelen a subsystem is supposed to emerge a warning when local adaption fails to handle the problem, e.g. if a small team of firefighters cannot confine a fire in their assigned area.

Carlos Gershenson told us about "Living in living cities"[4]. One of the challenges of 21st century is preventing the problems in the ultra-fast growing cities all over the world.
These are non-stationary (changing problems), traditional algorithms do not work well. Such challenges are for example urban mobility, logistics, telecommunications, governance, safety, sustainability, society and culture. A solution is to exploit properties of living systems, which are adaptive, learning, evolving, robust, autonomous, self-repairing, and self-reproducing, and to understand cities metaphorically as organisms.
Engineering methods cannot find a single solution to these changing problems. Instead it is necessary to constantly adapt the solution, thus have a self-organizing solution to a complex problem. Will cities become the "killer app" of cybernetics and systems research?
Discussion arose around the following issues:
But how do you get the officers and responsibles of a city to cooperate? There is a need for a strong motivation to overcome the inertia of the system.
Could cities instead built from scratch? No, because of the legacy issues - it is not possible to just tear down a large city and build it anew every few decades.
Can we prove that the system is robust against malicious behavior? Difficult since such a complex system cannot be easily predicted for all sets of possible inputs.
Are explicit measures necessary or would people themselves care for the necessary adaptations? This would not increase living standard for the people.

Anita Sobe presented ideas on self-organizing content sharing at social events by such interesting examples as the marriage of Kate and William of Windsor or Barack Obama's inauguration[5].
The presented approach allows people to share their self-generated content like photos or short videos instantly at such events. Existing platforms like flickr or youtube do not provide this liveness since most content is uploaded with a few days delay. The proposed approach organizes the content using an artificial hormone system. The hormone distribution is sensitive to the quality of a network connection and therefore, reflects a quality-of-service for a network path. The system is solely based on local decisions for forwarding, replicating and moving content. Over time, the content distribution in the network gets optimized in order to support short response times for requesters. Simulations show that the system competes well to other epidemic information dissemination methods such as Gossip.
The follow-up discussion brought up interesting questions:
How is overhead reflected in the simulation? Currently overhead is implicitly modeled into the transmission cost, which is valid for a constant packet handling overhead.
Furthermore the relation of the hormone-based approach to an ant colony optimization (ACO) algorithm was discussed. We identified a major difference to ACO, since there typically either the network or the content is assumed to be static. However ACO could be extended to handle the described scenario, which might inspire future work.
What is the effect, if tags are (more) complex? The system was started with a predefined tag hierarchy which can be extended to a more complex tag hierarchy. However, with more complex tags there is no guarantee for finding content.

In the last talk, Wilfried Elmenreich gave a talk on evolving a distributed control algorithm for flying UAV drones for a coverage problem[6]. The problem of having multiple mobile agents covering (or as we say in robotics, "sweeping") an area is relevant for many applications like lawn mowing, snow removal, floor cleaning,  environmental monitoring, communication assistance and several military and security applications.
The work by Istvan Fehervari, Wilfried Elmenreich and Evsen Yanmaz described a simple grid-based abstraction of the problem which was used to test two evolved and one handcrafted control algorithm which were compared to  reference algorithms like random walk and random direction.
A short summary of Wilfried's talk and the slides are available here.
The talk triggered interesting discussion involving the comparison with the “belief-based” algorithm. A further question triggering future work is on the influence on the layout and number of sensors. What will happen if the environment changes? Since the algorithm has no memory of a map, a changing environment does not affect the result.

References

1. B. McMullin, T. Hasegawa. Von Neumann Redux: Revisiting the Self-referential Logic of Machine Reproduction Using the Avida World. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.
2. V. Sesum-Cavic, M. Tuba, and S. Rankow. The Influence of Self-Organization on Reducing Complexity in Information Retrieval. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.
3. S. van Splunter, B. van Veelen. Coordination and Self-Organisation in Crisis Management. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.
4. C. Gershenson. Living in Living Cities. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.
5. A. Sobe, W. Elmenreich, and M. del Fabro. Self-organizing content sharing at social events. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.
6. I. Fehérvári, W. Elmenreich, and E. Yanmaz. Evolving a team of self-organizing UAVs to address spatial coverage problems. In R. M. Bichler, S. Blachfellner, and W. Hofkirchner, editors, European Meeting on Cybernetics and Systems Research Book of Abstracts, Vienna, Austria, April 2012.

Evolving a Team of Self-organizing UAVs to Address Spatial Coverage Problems

Typical small UAV (AscTec Pelican)

Coordinating a team of agents, which could be a search team, cleaning robots, flying drones for surveillance or environmental monitoring is a highly relevant problem. If the environment is unknown or subject to change, an a priori planning algorithm becomes difficult to apply. Therefore we looked into decentralized self-organizing algorithms to do the job.
In a joint work with István Fehérvári, Evsen Yanmaz and Wilfried Elmenreich (me), we evolve controllers for a team of unmanned aerial vehicles (UAVs) with the task to observe or cover a partially obstructed area.
The respective agents are limited in their sensory inputs to local observations of the environment without the ability to determine their absolute position or those of others. Each agent is equipped with a number of sensors that can detect the presence of other agents, an obstacle and the border of the area.

Simulation and evaluation model

The controller of an agent is implemented as an artificial neural network. The fitness for a given configuration is derived from the average spatial coverage over several simulation runs. The area coverage performance of the evolved controllers with different number of sensors is compared to reference movement models like random walk, random direction, and an algorithm based on the belief of the intention of agents met during the execution of the simulation. Our results show that evolved controllers can create a self-organizing cooperating team of agents that exploit the advantages provided by their sensors and outperform naïve coverage algorithms and also reach the performance of a recent algorithm that is using additional information as well.

The work was presented in a talk at the European Meeting on Cybernetics and Systems Research (EMCSR 2012) in Vienna, Austria. Slides are available via slideshare:

Evolving a Team of Self-organizing UAVs to Address Spatial Coverage Problems from Wilfried Elmenreich

View more presentations from Wilfried Elmenreich.

6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)

 CALL FOR PAPERS
6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012)
Lyon, France
10-14 September 2012
http://saso2012.univ-lyon1.fr 

Important Dates
******************
Abstract submission: April 23rd, 2012
Full paper submission: April 30rd, 2012
Notification of acceptance : June 20th, 2012

Introduction
*************
The aim of the SASO conference series is to provide a forum for presenting the latest results about self-adaptive and self-organizing systems, networks and services. To this end, the meeting aims to attract participants with different backgrounds, to foster cross-pollination between research fields, to expose and discuss innovative theories, frameworks, methodologies, tools, and applications, and to identify new challenges. The complexity of current and emerging computing systems has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, biology, etc.) to find new ways of designing and managing networks, systems and services. In this endeavor, self-organization and self-adaptation have emerged as two promising interrelated facets of a paradigm shift.

Self-adaptive systems work in a top down manner. They evaluate their own global behavior and change it when the evaluation indicates that they are not accomplishing what they were intended to do, or when better function or performance is possible. A challenge is often to identify how to change specific behaviors to achieve the desired improvement. Self-organizing systems work bottom up. They are composed of a large number of components that interact locally according to typically simple rules. The global behavior of the system emerges from these local interactions. Here, a challenge is often to predict and control the resulting global behavior.

Topics of Interest
*******************
The SASO conference is interested in both theoretical and practical aspects of systems exhibiting self-* characteristics. A particular focus is the modeling of natural, man-made and social systems that exhibit self-adaptation and self-organization characteristics as well as the constructive use of the underlying basic principles in technical systems. The sixth edition of SASO particularly encourages submissions from the following, non-exclusive list of topic areas:

- Principles, Theory, Methods and Architectures for SASO Systems
- Robustness, Resilience and Fault-Tolerance in/with Self-* Systems
- Self-* Behavior in Communication Networks
- (Self-)Control, (Self-)Observation, (Self-)Monitoring of Engineered Systems
- Collective Phenomena in Social and Socio-Technical Systems
- Self-Organization and Self-Adaptation in Biological/Natural Systems
- Applications of Spatial and Physics-Inspired Self-Organization
- SASO Principles in Cyber-Security
- SASO Principles in Collective Robotic Systems
- SASO Principles in Cyber-Physical Systems
- Real-World Experience with Engineered Systems Exhibiting Self-* Properties

All contributions must present novel theoretical or experimental results, or practical approaches and experiences in building or deploying real-world systems and applications. Contributions that contrast "conventional" engineering principles with novel approaches making use of SASO principles are especially welcome.

Submissions Instructions
****************************
All submissions should be 10 pages and formatted according to the IEEE Computer Society Press proceedings style guide and submitted electronically in PDF format. Please register as authors and submit your papers using the SASO 2012 conference management system. The proceedings will be published by IEEE Computer Society Press, and made available as a part of the IEEE digital library. Note that a separate call for poster and demo submissions has also been issued.

Emerging Topic Papers
**************************
In addition to regular papers, SASO also encourages the submission of papers on emerging topics. These submissions should be clearly marked as such (indicating "Emerging Topic:" in the title) and should provide a well-rounded survey of novel questions, methods and abstractions that are relevant for the design of SASO systems along with a clear indication of the possible impact on the SASO community. In this category we particularly encourage submissions that present innovative applications of methodological frameworks being used in other fields of science that study SASO related phenomena, thus highlighting connections and potential for collaboration between different scientific communities.

Review Criteria
*****************
Papers should present novel ideas in the topic domains listed above, clearly motivated by problems from current practice or applied research. We expect claims of contribution to be clearly stated and substantiated by formal analysis, experimental evaluations or comparative studies. Appropriate references must be made to related work. Since SASO is a cross-disciplinary conference, a particular criterion that will be strictly enforced by the program committee is that all papers must be understandable by researchers that are not members of the particular, highly-specialize scientific community. Emphasis should rather be placed on cross-cutting aspects that are relevant to a wider audience of researchers and engineers dealing with SASO systems. Furthermore, submissions making use of principles inspired by phenomena occurring in fields like biology, physics, sociology, economics, etc. are required to provide references for all relevant work in the respective field. Papers demonstr
ating SASO principles in practical applications are expected to provide an indication of the real world relevance of the problem that is solved, including some form of evaluation of performance, usability, or superiority to alternative state-of-the-art approaches. If the application is still early work in progress, then the authors are expected to provide strong arguments as to why the proposed approach will work in the chosen domain.

The program committee strongly suggests to review the list of common reasons for SASO submissions being rejected, which is available online. Furthermore, a collection of interdisciplinary approaches to the study of SASO-related phenomena is provided. Prospective authors are invited to check whether their research question can be related to this rich body of work, thus benefiting from tools, methods and findings developed in various disciplines.

Technical Meeting Committee
********************************
General chairs
Salima Hassas, Universite Claude Bernard-Lyon 1, France
Paul Robertson, DOLL, USA

PC chairs
Anwitaman Datta (Distributed Systems), NTU, Singapore
Marie-Pierre Gleizes (Self-organization), Universite de Toulouse, France
Ingo Scholtes (Socio-tecnical Systems), ETH Zurich, Switzerland

Local chair
Gauthier Picard, Ecole Nationale Superieure des Mines de Saint-Etienne

Finance chair
Frederic Armetta, Universite Claude Bernard-Lyon 1, France

Poster chair
Stefan Dulman, Univ. Delft, Netherlands

Contest and Demos track Chairs
Olivier Simonin, LORIA, France 

Antonio Coronato, ICAR-CNR, Italy

Workshop chair
Jeremy Pitt, Imperial College London, UK

Tutorial chair
Giuseppe (Peppo) Valetto, Drexel University, USA

Publicity chair
Jose Luis Fernandez-Marquez, Univ. Geneva, Switzerland
Zhang Jie, Univ. Singapore, Singapore
Sam Malek, George Mason Univ., Fairfax, USA

Publication chair
Sven Brueckner, Jacobs Technology Inc., USA

Sponsor chair
Bob Laddaga, DOLL, USA

Web and Wiki chair
Haytham El Ghazel, Universite Claude Bernard-Lyon 1, France

Symposium on Self-* Systems – Biological Foundations and Technological Applications

Symposium on Self-* Systems – Biological Foundations and Technological Applications

part of EMCSR 2012, the 21st European Meeting on Cybernetics and Systems Research

April 10-13, 2012, Vienna, Austria

http://www.emcsr.net/

Call for papers

Part 1. Biologically and Socially Inspired Self-* Systems

Chairs: Vesna Sesum-Cavic, Institute of Computer Languages, Vienna University of Technology, Vienna, Austria, and Carlos Gershenson, Instituto de Investigaciones en Matemáticas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico

The increased complexity in today’s’ IT industry is one of the top problems and important obstacles. Self-organization appears as one promising way to cope with the increased complexity. Generally, self-* systems should posses as many self-* properties as possible (self-healing, self-tuning, self-learning,…) in order to achieve self-organization. Self-organization surrounds us. Many interesting self-mechanisms exist in our environment from which we can learn a lot. A careful observation of mechanisms in nature and society can discover some new tools that could beneficially be applied to different IT-problems. This conference track will focus on both biologically and socially based self-* systems. The papers could be theoretically based as well as with practical applications to important IT-problems.

Session 1: Biologically Inspired Self-* Systems (chair: V.C.)
Session 2: Socially Inspired Self-* Systems (chair: C.G.)

For further information contact vesna@complang.tuwien.ac.at and cgg@unam.mx.

Part 2. Self-Organizing Networked Systems

Chairs: Wilfried Elmenreich, Networked and Embedded Systems, Alpen-Adria-Universität Klagenfurt, Austria, and Carlos Gershenson, Instituto de Investigaciones en Matemáticas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico

Part 2 of this symposium will present and discuss current and novel approaches for applications of self-organizing systems.

A self-organizing system typically consists of many networked entities that organize themselves and cooperate through the exchange of information without the need of a centralized control instance but using a distributed approach. Information is exchanged locally among individual entities in the frame of the fulfillment of a certain global objective. Some simple and high-level rules in the individual entities lead to sophisticated functionality of the overall system. Many examples of successful distributed localized organization can be found in nature (e.g., ants, fireflies).

Self-organizing systems have various favorable properties:

• They typically adapt very easily to changes from inside and outside the system.
• Additional entities can be added and will be assimilated into the global system.
• Entities may be removed without too much affect on the global system, and other entities may take over crucial tasks of them.
• Furthermore, self-organizing systems scale very well and there is no bottleneck of a central authority.

Research into self-organizing networked systems not only has technical and user-oriented aims, it also enables a high degree of interdisciplinarity.

We encounter self-organizing systems on an almost daily basis in:

• the formations of swarms of fish and migratory birds
• the interplay of termites when they build their hills
• the activity of body cells during the healing of wounds.

In many areas of nature, single individuals or organisms work together without central coordination, but in perfect harmony. Large areas of the economy have already been functioning for many years according to this paradigm.

It is the aim of this symposium to create a forum for exchanging ideas, discuss solutions and share experiences among researchers and developers of self-organizing systems applications.
For further information contact wilfried.elmenreich@uni-klu.ac.at and cgg@unam.mx.

Confirmed keynote speakers include Edgar Morin, Péter Csermely, and Péter Érdi.

Submission details:

For submission and conference details, please visit http://www.emcsr.net/?page_id=55

Important Dates:

Submission deadline: January 14, 2012 extended to January 20, 2012
Notifications:             January 27, 2012
Schedule published:   February 7, 2012
Conference:                April10-13, 2012