New Book: Engineering Swarms of Cyber-Physical Systems

We are excited to announce the release of our new book, Engineering Swarms of Cyber-Physical Systems, published by CRC Press in 2025. Authored by Melanie Schranz, Wilfried Elmenreich, and Farshad Arvin, this book is a vital resource for researchers, engineers, and students interested in swarm intelligence and cyber-physical systems (CPS).

This comprehensive guide covers the entire design cycle for applying swarm intelligence in CPS, including modeling, design, simulation, and deployment. Key features include:

• Real-World Examples: Applications in robotics, manufacturing, and search and rescue.
• Hands-On Approach: Programming examples that facilitate quick implementation of concepts.
• Diverse Methodologies: Insights into classical and machine-learning design methods for swarm applications.
• Simulation Insights: A chapter dedicated to simulation requirements and models.

 

Why We Wrote This Book

After years of research, we felt the need for a comprehensive resource that combines theoretical insights with practical applications. Our goal is to inspire creativity and provide the tools necessary for readers to embark on their own projects.

We invite you to explore Engineering Swarms of Cyber-Physical Systems yourself. We hope this book serves as a valuable resource for your research and engineering endeavors!

 

Melanie Schranz, Wilfried Elmenreich, Farshad Arvin. Engineering Swarms of Cyber-Physical Systems. CRC Press 2025. ISBN 978-1-032-04715-7. 

A Slime Mold Algorithm for Repairing a Power Transmission Network after an Electromagnetic Pulse Attack

After an extensive journey of in-depth exploration, spanning literature review, hypothesis formulation, modeling, implementation, and many weeks of simulation, Kristina Wogatai proudly presented her paper, "A Graph-Based Approach for Applying Biologically-Inspired Slime Mold Algorithms for Repairing a Power Transmission Network after an Electromagnetic Pulse Attack," at the 2nd International Conference on Power Systems and Electrical Technology (PSET) in Milan, Italy, held from August 25th to 27th, 2023. The paper, authored by Kristina Wogatai, Johannes Winkler, and Wilfried Elmenreich, explores how to apply slime mold algorithms to restore power grids after an electromagnetic pulse (EMP) attack.

Our proposed method intricately utilized a simulated slime mold algorithm on graph models to pinpoint critical repair areas, drawing inspiration from how slime molds construct networks between food sources. These single-celled organisms, known for their intelligent swarm behavior, have inspired algorithms addressing optimization problems and the creation of efficient transportation networks. Our open-source algorithm, SISMO (Simulation of Slime Molds), has contributed to this work.

Adapting the SISMO algorithm for connecting power stations and plants required overcoming challenges, such as incorporating geographic or demographic criteria for power line placement. Initially provided only with the positions of power stations, we addressed this problem by leveraging graph visualization algorithms like Force Atlas, Force Atlas2, and Yifan-Hu to modify the layout and thus communicate these parameters to the algorithm effectively.

Our efforts did not go unnoticed, as Kristina received the Best Oral Presentation Award at the conference, emphasizing the paper's quality and the significance of its findings in power network restoration.

For further information, check out the paper

Kristina Wogatai, Johannes Winkler, and Wilfried Elmenreich. A Graph-Based Approach for Applying Biologically-Inspired Slime Mold Algorithms for Repairing a Power Transmission Network after an Electromagnetic Pulse Attack. In Proc. 2023 2nd International Conference on Power Systems and Electrical Technology (PSET 2023), Milan, Italy, August 25-27, 2023.

SwarmFabSim: A simulation framework for bottom-up optimization in flexible job-shop scheduling using Netlogo

It was great to be in presence at a conference again. At the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, aka SIMULTECH, we presented our paper 

Martina Umlauft, Melanie Schranz, and Wilfried Elmenreich. SwarmFabSim: A simulation framework for bottom-up optimization in flexible job-shop scheduling using Netlogo. In Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH. SciTePress, July 2022. (doi:10.5220/0011274700003274) 

Click triangle for Bibtex entry

@inproceedings{umlauft:swarmfabsim:22,
  author = {Umlauft, Martina and Schranz, Melanie and Elmenreich, Wilfried},
  title = {{SwarmFabSim}: {A} Simulation Framework for Bottom-up Optimization
in Flexible Job-Shop Scheduling Using {N}etLogo},
  booktitle = {Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH},
  year = {2022},
  month = jul,
  publisher = {SciTePress},
  doi = {10.5220/0011274700003274},
}
  

The paper shows how to the programming language NetLogo to model and simulate a factory producing according to the job-shop manufacturing principle. The main contribution is a modular simulation framework that can apply various algorithms to optimize a make-to-order manufacturing system and supports multiple configurable scenarios. The evaluation framework was used to assess the effectiveness of an artificial hormone algorithm compared to a naïve basic implementation and a reference baseline algorithm. The evaluation was based on three key performance indicators: Flow factor, delay, and utilization. The simulations show promising results of the artificial hormone algorithm in three reference scenarios with significant improvements over the reference algorithms. The implementation of the simulation environment is published as open source in the Git repository https://swarmfabsim.github.io. Readers are welcome to contribute with their ideas and developments.

Screenshot of the SwarmFabSim application

An Artificial Hormone-based Algorithm for Production Scheduling

Artificial hormone systems are inspired by the natural endocrine system that adjusts the metabolism of tissue cells in our body. By connecting decisions and actions in a system to the production and evaporation of artificial hormones, it is possible to create a bio-inspired self-organizing algorithm.

Application areas for such algorithms are problems with many agents to be coordinated, where existing optimization approaches come to their limit. An example of such a problem is the production of logic and power integrated circuits (ICs) in the semiconductor industry. Unlike the high-volume production of memory ICs, wafer production in the logic and power sector has a large product mix. This involves many processing steps and dynamic changes of involved machines.

Weekly workloads can involve around 100 000 operations on thousands of machines. Optimizing such a system for work in progress and flow factor is an NP-hard problem. At this size, existing dispatching rules and linear optimization methods cannot cope with the NP-hard search space, thus not optimize the entire system.

To address this issue, we have modeled a production plant as a self-organizing system of agents that interact with each other in a non-linear way. As it is common in the semiconductor industry, wafers are combined in groups of 25 pieces forming a so-called lot. In our approach, an artificial hormone systems is used to express a lot's urgency and the need for new lots at a machine type, thus providing a system using local information for optimization. The algorithm builds upon five principles, which are 

• (i) machines produce hormone to attract lots, 
• (ii) hormone diffuses process-upstream, 
• (iii) incoming lots diffuse hormone, 
• (iv) lots are prioritized by their timing, and 
• (v) lots are attracted by hormone. 

Via these mechanisms, machines can balance their workload by pulling required lots towards them. The algorithm has been implemented and evaluated in a NetLogo simulation model. Simulation results indicate that the artificial hormone system improves around 5% for overall production time and flow factor compared to a baseline algorithm. Future work will investigate if the hormone algorithm can be used on top of existing production systems. In a productive system an improvement of 5% would be highly notable.

More information can be found on the SWILT project webpage and in the paper

Wilfried Elmenreich, Alexander Schnabl, and Melanie Schranz. An artificial hormone-based algorithm for productionscheduling from the bottom-up. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence. SciTePress, February 2021.

Click triangle for Bibtex entry

@inproceedings{elmenreich:Hormone:21,
  author = {Elmenreich, Wilfried and Schnabl, 
    Alexander and Schranz, Melanie},
  title = {An artificial hormone-based algorithm
    for production scheduling from the bottom-up},
  booktitle = {Proceedings of the 13th International 
    Conference on Agents and Artificial Intelligence},
  year = {2021},
  month = feb,
  publisher = {SciTePress}
}  
  

Benford’s Law and the US 2020 Presidential Election Votes

Benford’s law states that if you get a big range of data from the real world and you look at the lead digit of each of the values you get significantly more 1s than other digits if the numbers span multiple magnitudes.

As one application, Benford’s law is used to detect fraud in accounting. There typically, the pairs of the two first digits are analyzed and plotted according to their frequency in order to detect anomalies. An anomaly can have different explanations though.

For example, in the US 2020 presidential elections, the proportion of digits 1 and 2 on first digits for votes for Mr. Biden is lower than expected, while for votes for Mr. Trump the proportion of digits 1 and 2 on first digits is slightly higher.

In the video below, Matt Parker analyzes the situation and shows that the more densely populated areas in the US, where a majority of Mr. Biden's votes are coming from, have precincts with mostly the same size. Thus here the condition of having data spanning multiple magnitudes is not fulfilled, hence we get a distribution of first digits that deviates from the prediction by Benford’s law.

When looking at the frequency of the last digits, there is an anomaly in the voter data for Mr. Trump. Instead of having a roughly equal distribution of frequency of last digits, the lower digits are much higher. This is due to the fact that a majority of votes for Mr. Trump come from smaller precincts thus favoring the smaller numbers.

 

Thus, the deviation of voting counts (from precincts with a standardized size) from Benford’s Law is not an indicaton of voter fraud but rather a phenomenon to be expected.

Further reading:
Deckert, J., Myagkov, M., & Ordeshook, P. (2011). Benford's Law and the Detection of Election Fraud. Political Analysis, 19(3), 245-268. doi:10.1093/pan/mpr014

Two Open PhD Student Positions at Alpen-Adria-Universität Klagenfurt, Austria

The Institute of Networked and Embedded Systems at the University of Klagenfurt, Austria, has an opening for two researchers (PhD student) in Self-Organizing Networked Systems.

You will work in an European project on Cyber-Physical Systems. The project duration is three years. Research will be conducted at the Smart Grids group at the Institute of Networked and Embedded Systems under the supervision of Professor Wilfried Elmenreich. Working language is English. The institute cooperates with national and international partners from industry and academia and is part of the research cluster Lakeside Labs (self-organizing networked systems).

Our team is very international and dedicated to quality research and teaching. The offices and laboratories are located in the well-equipped Lakeside Science & Technology Park. Working language is English. The Institute cooperates with national and international partners in research and industry. It is part of the research cluster Lakeside Labs on self-organizing networked systems.

The candidate is expected to have a master in electrical or computer engineering, computer science, applied mathematics or equivalent. Experience in one or more of the following fields is required:

• Distributed and swarm algorithms
• Genetic algorithms and evolutionary design
• Very good programming skills in Java

The contract will be based on 30 hours per week with a gross salary of at least 28314 EUR per year. Please mail applications containing a letter of interest, curriculum vitae, copies of academic certificates and courses, list of publications, and contact details of two references in a single PDF file to wilfried.elmenreich@aau.at before January 12, 2016. Women are especially encouraged to apply.

Tools for Calculating Academic Collaboration Distance

I think most of you have heard about the Erdös number. The Erdös number is the number of edges between you an Erdös in an author collaboration graph.
This is an undirected network where every published paper defines egdes between their authors. Having a low Erdös number somehow became a status symbol for researchers. Since Erdös already passed away, there is no way to get an Erdös number of one today, unless you hope for a Zombie apocalypse with the death rising:

Excerpt from "Apocalypse" by Randall Munroe at xkcd.com under CC-BY-NC 2.5

Due to Paul Erdös' outstanding publication productivity, there are quite a number of people with an Erdös number of 1, so if you find the right collaborator, you can reach an Erdös number of 2, if you like. But even beyond the fad on Erdös numbers, author collaboration graphs and distances between authors are an interesting way to define closeness between the work that two academics are doing.

What are good tools to calculate author collaboration distance?

There is MathSciNet, but their database only includes mathematical journals. Since my research is mostly published in computer science/embedded systems journals, this site doesn't work for me.
The zbMATH page offers a similar tool, again it seems to include only mathamatical journals. I should publish more there.

Previously, Microsoft Academic Research had a nice author collaboration search that graphically displayed the connections between any two authors. However, this feature is currently not available, since the page was restructured to work without the Silverlight plugin. I hope the feature comes back someday.

Distance calculator at csauthors.net

Currently, the best tool for computer scientists is the distance calculator at csauthors.net. It works with a database that seems to be more complete than the ones used by the sites cited above. The database is however far from being complete, so that distances are sometimes reported to be longer than they actually are.

My Erdös number

Thanks for asking! It is 3, for example via the following papers:

• W. Elmenreich, R. D'Souza, C. Bettstetter, and H. de Meer. A survey of models and design methods for self-organizing networked systems. In Proceedings of the Fourth International Workshop on Self-Organizing Systems, volume LNCS 5918, pages 37–49. Springer Verlag, 2009.
• D. Achlioptas, R. M. D'Souza and J. Spencer, "Explosive Percolation in Random Networks", Science, 323 (5920) 1453-1455, 2009.
• P. Erdös and J. Spencer. Imbalances in k-colorations. Networks, Volume 1, Issue 4, Pages 379–385, 1971 

All papers are on the topic of networks or networked systems. How fitting.

Top Journals in Multidisciplinary Science

Alex Vespignani says it briefly and concise in his tweet: for those who are fans of rankings, this would be the ten top journals in multidisciplinary science:

These are for sure great Journals to publish in, but the fact that you do work in a multidisciplinary area does not necessarily endorse you to publish in a particular journal on this list, even if your work is excellent. However, it is definitely worth to check out these journals and learn what makes them so important (this advise of course contributes to the Matthew effect :-) ).
Hope to read from you in one of these journals soon!

See also You don’t cite me anymore - Scientific publications and the ravages of time.

Five postdoctoral fellowships in complex systems, Mexico

The Center for Complexity Science of the National Autonomous University of Mexico is seeking outstanding candidates for five one year postdoctoral positions beginning in August, 2015. Research plans from all areas related to complex systems are encouraged.

Please send CV and research plan to cgg [at] unam.mx before June 10th.

Original post: Complexes: Five postdoctoral fellowships in complex systems, UNAM

FREVO 1.2 release

We proudly announce the new release 1.2 of FREVO (FRamework for EVOlutionary design). FREVO helps 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 supports decomposing the task into problem definition, solution representation and the optimization method. The componentwise separation allows to experiment with different combinations of algorithms and neural networks for different tasks.

The following components were added to FREVO:

• HEMS – a simulation for modeling trading behavior of loads and local energy generators.
• SinglePong – a simulation of the one player pong game where several paddles can cooperate in order to achieve better performance.
• Pong – a simulation of the pong game where two teams can play against each other.

Quick start:

• download the newest version at frevo.sourceforge.net 
• unpack the ZIP file
• unless you have it already on your system, install Java 
• execute the createscrips.jar ("java -jar createscrips.jar") 
• you can now run FREVO using the script named launch_Frevo 

...or have a look at the following video explaining the basic steps to get started with FREVO:

For more information see the following sources:

• A. Sobe, I. Fehérvári, and W. Elmenreich. Frevo: A tool for evolving and evaluating self-organizing systems. InProceedings of the 1st International Workshop on Evaluation for Self-Adaptive and Self-Organizing Systems, Lyon, France, September 2012.
• A. Monacchi, S. Zhevzhyk, and W. Elmenreich. HEMS: A home energy market simulator. Computer Science - Research and Development, 2014. 
• I. Fehérvári and W. Elmenreich. Evolving neural network controllers for a team of self-organizing robots. Journal of Robotics, 2010.
• FREVO - software used for the evolutionary algorithm.
• WMOrakel - the championship between self-organized soccer teams which were evolved using FREVO.

Self-organizing Processes in Physical Geography

In this talk, Marco van der Wiel presents some ideas on self-organization and self-organized criticality, and how these relate to physical geography and (explanatory and exploratory) modelling in physical geography.

Loading video...

The talk is in english, you might want to skip the german introduction until 1:40. Video by AAU Campus TV/Egmont Sparouz.

The Next Big Thing in Artificial Evolution

As announced in a previous blogpost, Prof. A. E. Eiben gave a very interesting talk on the next big in thing in artificial evolution during his visit at the Alpen-Adria-Universität Klagenfurt. Eiben presented a vision about having animate artefacts that are able to evolve and self-reproduce in physical spaces. To make this happen, he gives a notion of the integration of "hard" vs. "soft" evolutionary computation, the former meaning evolutionary optimiziation and design while the latter refering to artificial life, swarm robotics, and artificial societies.

Gusz Eiben's talk was attracting many people and lead to a vivid discussion afterwards about technology, possibilities, societal implications and parallels to existing sci-fi stories from Philip K. Dick or movies such as Terminator. So I think it is appropriate to say this talk was truly presenting science beyond fiction.

• A.E. Eiben, S. Kernbach, and Evert Haasdijk, Embodied artificial evolution: Artificial evolutionary systems in the 21st Century, Evolutionary Intelligence, 5(4):261-272, 2012
• A.E. Eiben. Introduction on Evolutionary Computing, Book, Springer, Natural Computing Series, 2003, ISBN: 3-540-40184-9
• More information on Eiben's work

Prof. A. E. Eiben at Lakeside Labs: The Next Big Thing in Artificial Evolution

Professor Àgoston E. Eiben will give an interesting talk at the Lakeside Labs / Alpen-Adria-Universität Klagenfurt on April 10th 2014, 15:00 CET, Room L4.1.114  

Abstract:
This talk presents a vision about the upcoming breakthrough in artificial evolution: animate artefacts that (self-)reproduce in physical spaces. In other words, we witness the “Evolution of Things”, rather than just the evolution of digital objects, leading to a new field of Embodied Artificial Evolution. After presenting this vision some of the technical challenges are elaborated and related to the main algorithmic/technical requirements to the current know-how in evolutionary computing. Finally, Prof. Eiben will speculate about possible applications, their societal impacts, and argue that these developments will radically change our lives.

For those who cannot attend or want to warm up on the topic, we recommend Eiben's TED talk "Evolution at Work":

Bio:
A.E. Eiben is a professor of Computational Intelligence on the VU University Amsterdam and Visiting Professor in the Department of Electronics of the University of York, UK. He is one of the European early birds of Evolutionary Computing; his first EC paper dates back to 1989 and he co-authored the first comprehensive book on the subject. He has been organizing committee member of practically all major international evolutionary computing conferences and editorial board member of related international journals. He have also coordinated or participated in several EU research projects. Prominent themes in his work include multi-parent recombination methods, evolutionary constraint handling, evolutionary art, artificial life, and evolutionary robotics. Furthermore, he is concerned with methodological issues, especially the design and calibration of evolutionary algorithms (parameter tuning off-line as well as parameter control on-line). Lately he became interested in artificial evolutionary systems that are physically embodied in real time and real space. This goes far beyond conventional evolutionary computing in digital spaces and implies great new opportunities and challenges – see his TEDx talk and a journal paper on the vision, and the The Triangle of Life framework for a possible implementation in robotic systems that can self-reproduce. On the long term, a broad range of possible “incarnations” can emerge and form a radically new way of engineering. Furthermore, they can serve as an apparatus to investigate deep scientific questions about evolution in a new substrate, different from carbon-based life as we know it.

Solving the „Tracking Game“

Guest article from Doris A. Behrens


Games taking place in a shared environment are characterized by the fact that the effectiveness of individual decisions heavily depends on the decisions of other players. Our algorithm OPTGAME is able to approximate the evolution of choices to be made if a number of independent decision makers seek to reach individually desirable states. The evolution of states subject to control is described by a system of nonlinear difference equations. We call this a „tracking game“, since is an extension of the linear regulator problem (also known as „tracking problem“) that is well known from LQ optimal control theory.
OPTGAME is a tool that steers the control and state paths towards desired outcomes. It is novel in a way that it works for game theoretic systems with nonlinear constraints. It searches for equilibrium solutions by iteratively applying a sequence of local linearization and optimization over the entire planning horizon. The tool yields three types of non-cooperative equilibrium solutions (open-loop Nash equilibrium, feedback Nash equilibrium, feedback Stackelberg equilibrium) plus one cooperative solution (Pareto-optimal strategy).
An example for such a game could be the decision-making within a monetary union such as the European Monetary Union (EMU). In this game all but one player represent countries with intentions for economic growth, employment and limited budget deficit and one player represents the European Central Bank, aiming solely at price stability. Besides trade-offs between state variables, for example the well-known trade-off between unemployment and price stability (see Phillips curve), there are strong economic interdependencies due to international trade.

European Monetary Union

For instance, if a single country aims at economic growth, one option could be to increase the demand for goods and services from the public sector. This increases production in response to demand, which in turn increases incomes. However, within an open economy the future success strongly depends on the situation and behavior of the other member countries. In order to find a solution for this problem it is necessary to estimate the countries’ individual parameters as well as the degree of economic interdependencies (like trade) between countries.
Such models, in order to be accurate are inherently nonlinear, which cannot be solved analytically by a linear model such as the LQ game. In our work we apply OPTGAME to a monetary union macroeconomic model based on the nonlinear MUMOD1 model. In this model, there are basically two groups of countries, one economically stronger than the other, all experiencing a brief period of recession.

Doris A. Behrens is a senior re-
searcher working on optimization
in techno-socio-economic systems
at the Alpen-Adria-Universität
Klagenfurt

Without policy intervention all countries would experience a deep recession and an enormous increase in public debt. By applying OPTGAME for different solution concepts we learn that macroeconomic properties like public debt, economic growth, inflation, etc. can be significantly improved with system-aware control actions of players.

The OPTGAME tool is available as MATLAB implementation upon request (Contact Doris A. Behrens).

Literature:

Doris A. Behrens, Reinhard Neck, Approximating Solutions for Nonlinear Dynamic Tracking Games, Computational Economics, Springer, February 2014. DOI: 10.1007/s10614-014-9420-4

Reinhard Neck, Doris A. Behrens, A macroeconomic policy game for a monetary union with adaptive expectations. Atlantic Economic Journal, 37(4), 335–349, 2009. DOI: 10.1007/s11293-009-9186-6f

Interactive web resources on Self-Organizing Systems

WATOR Predator-Prey Simulation

WATOR is a simulation of the interaction over time of predator and prey in a small rectangular area

Language: Java (runs in Browser)
http://www.leinweb.com/snackbar/wator/

Fish School and Predator

This is a simulation of a fish school, where each fish tries to align to its comrades, forming a fish swarm after some time.

Language: Scratch (runs in Browser via Adobe Flash)
http://scratch.mit.edu/projects/10734382

Ant Simulator

Simulation of virtual ants looking for food.

Language: Java (runs in Browser)
http://newton-nes.uni-klu.ac.at/~wilfried/ants/

Conway's Game of Life

Interactive cellular automata simulation.

 Language: Java (runs in Browser)
http://www.bitstorm.org/gameoflife/

Foxes and Rabbits Predator-Prey System

Simulation of a small ecosystem involving a fast-breedin prey (rabbits) and predators (foxes) feeding on them.

Language: Scratch (runs in Browser via Adobe Flash)
http://scratch.mit.edu/projects/10699259/

Slime Mold Simulation

Explanation: http://ccl.northwestern.edu/netlogo/models/Slime

Language: Netlogo (runs in Browser via Java)
http://ccl.northwestern.edu/netlogo/models/run.cgi?Slime.651.477

Fireflies

Explanation: http://ccl.northwestern.edu/netlogo/models/Fireflies

Language: Netlogo (runs in Browser via Java)
http://ccl.northwestern.edu/netlogo/models/run.cgi?Fireflies.763.498

Segregation

Explanation: http://ccl.northwestern.edu/netlogo/models/Segregation

Language: Netlogo (runs in Browser via Java)
http://ccl.northwestern.edu/netlogo/models/run.cgi?Segregation.734.460

Twitter Network Analysis

Interactiv webpage for analyzing trends on Twitter. 

 

Language: Javascript

http://truthy.indiana.edu/politics

The Complex Systems Community Explorer

If you are working in the field of complex systems, you face network analysis and graphical data representation. So why not use these features to organize your research network and to identify possible collaborators?
The complex systems community explorer developed at ISC-PIF by Julian Bilke and David Chavalarias is doing exactly this. In particular, it visualizes data are taken from the complex systems registry directory. This directory is an open directory maintained by several complex systems organisations and coordinated by the Complex Systems Society. After registering your data and interests, you can explore other scholars graphically. Links symbolize how semantically close two researchers are. The more shared keywords match, the stronger the link.

FREVO 1.0 released

We proudly announce the new release 1.0 of  FREVO (FRamework for EVOlutionary design). FREVO helps 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. These components allow to experiment with different combinations of algorithms and neural networks for different tasks.

The new version, FREVO 1.0, comes with 26 different components and an improved user interface which allows you to pause an evolution and check the intermediate results.

Quick start:

1. download the newest version at frevo.sourceforge.net 
2. unpack the ZIP file
3. unless you have it already on your system, install Java
4. execute the createscrips.jar ("java -jar  createscrips.jar")
5. you can now run FREVO using the script named launch_Frevo

...or have a look at the following video explaining the basic steps to get started with FREVO:

For more information see the following sources:

• 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. 
• I. Fehérvári and W. Elmenreich. Evolving neural network controllers for a team of self-organizing robots. Journal of Robotics, 2010.
• The DEMESOS project www.demesos.tk
• Software used for the evolutionary algorithm: FREVO www.frevotool.tk

POEtic-Cubes: Self-organizing Art

POEtic-Cubes is a physical installation consisting of 9 autonomous robots which are able to react to stimuli coming from its direct environment. Stimuli are either induced from other robots or come from people interacting with the robots. Although every robot has the same program, different stimuli and interaction with each other leads to an emergent process where the robots self-organize into an overall organism consisting of 9 cells. A similar effect of differentiation of behavior despite of identical programming can be found in the robot soccer example.

Nice art, nice robots, although a bit loud :-)

• Raquel Paricio, Juan  Manuel Moreno. POEtic-cubes: attention and emergence. Bio-inspired hardware for art installations. artnodes 9, 2009 (in spanish language)

Call for Papers 6th Complex Systems Modelling and Simulation Workshop (CoSMoS 2013)

Università degli Studi di Milano-Bicocca, Italy
1 day workshop held between 1 - 5 July 2013

http://www.cs.york.ac.uk/nature/cosmos/cosmos2013.html
cosmos2013-group@york.ac.uk

SPECIAL ISSUE OF NATURAL COMPUTING JOURNAL: we will be organising a special issue of the Natural Computing journal (http://www.springer.com/computer/theoretical+computer+science/journal/11047) based on the themes raised in the workshop. Suitable workshop submissions will be invited to submit to this special journal issue.

The 6th workshop on Complex Systems Modelling and Simulation (CoSMoS 2013) will take place as a 1-day satellite workshop of the Unconventional Computation and Natural Computation conference (http://ucnc2013.disco.unimib.it/) held between 1st and 5th July at the Università degli Studi di Milano-Bicocca, Italy. The CoSMoS workshops series provides a forum for research examining all aspects of the modelling and simulation of complex systems. This year, we will place a special focus on how complex systems simulations can be used to simulate unconventional and natural computation.

Constructing models and simulations of complex systems is a challenging and interdisciplinary task. Elements might include choice of modelling tools and techniques, simulation infrastructures, concurrency, the process of moving from models to simulations, arguing validity of simulations, and the identification of reusable engineering techniques such as patterns. The CoSMoS workshop series continues an initiative, based at the Universities of York and Kent, UK, to develop a framework and infrastructure for the construction of complex systems simulations.

Submitted papers will undergo a rigorous peer-review process and accepted papers will appear in the workshop proceedings published by Luniver Press. Proceedings of the previous CoSMoS workshop are available: http://www-users.cs.york.ac.uk/psa/cosmos2013/proceedings.html


AREAS OF INTEREST

We are seeking submissions that explore aspects of complex systems modelling and simulation, with a special focus on how complex systems simulations can be used to simulate unconventional and natural computation. Areas of interest include, but are not limited to:

* Complex systems simulation case-studies
* Modelling tools and techniques
* Simulation infrastructures
* Arguing validity of simulations
* Concurrency and distribution techniques
* Identification of reusable engineering techniques
* Working across scientific disciplines


SUBMISSIONS

We are accepting both full papers (to be presented orally) and abstracts (to be presented via a poster). Both full papers and abstracts will appear in the workshop proceedings.

For submission via abstract, please submit an abstract not longer than 2 pages of LNCS format that summarises the content of the poster you wish to present. Full papers can be of any length up to a maximum of 25 pages of LNCS format. If you wish to exceed the page limit, or have any other queries, then please email cosmos2013-group@york.ac.uk in advance of submission.

LNCS formatting details can be found here: http://www.springer.com/computer/lncs?SGWID=0-164-7-72376-0

Papers should be submitted via EasyChair here: https://www.easychair.org/conferences/?conf=cosmos2013


IMPORTANT DATES

* Paper Submission: 22 March 2013
* Notification of acceptance: 22 April 2013
* Camera ready copies: 6 May 2013
* CoSMoS Workshop: 1 day between 1 - 5 July 2013


WORKSHOP CHAIRS

* Paul Andrews, Department of Computer Science and York Centre for Complex Systems Analysis, University of York, UK
* Susan Stepney, Department of Computer Science and York Centre for Complex Systems Analysis, University of York, UK

You don’t cite me anymore - Scientific publications and the ravages of time

One of the most specific things about scientific literature is that scientific papers and books contain references to other papers. The number of citations has become an indicator for the impact of a result, the more other papers cite an article, the higher is its considered impact.

The number of citations a scientific paper gets is a result of interesting effects and interactions:

First, there is the Matthew effect, also known by the proverb "the rich get richer and the poor get poorer" can be observed, where a preferential attachment to larger nodes causing a power-law distribution of node degrees rather than a normal distribution which would be expected for any repeated random experiment with statistically independent trials. Due to this effect the average paper does not get the mean value of all citations, no, it gets close to zero. Most papers do not get more than 5 citations. But a few papers get cited a thousand times or even more often. Models assume that highly cited papers have a better chance of being cited in new papers can explain this behavior and predict a smooth power law distribution for paper citations.

However, to make the model accurate, there is another factor: time.

While the total number of citations for a given paper naturally can only increase over the years, the actual ability of papers to attract further citations dimishes over time - the paper "ages" (see Citation averages, 2000-2010). This applies even to classic papers, for example from Einstein or Hawking, which are no longer cited as they once were.

Matúš Medo and his colleagues from the University of Fribourg in Switzerland developed a model taking this aging factor into account. They found that a paper’s relevance decreases dramatically a few years after its publication.

Especially in our time of instant communication of results, it thus becomes very unlikely that a scientific paper gains in popularity after some time has passed. Sorry to crush your hopes, but if you have a meagerly cited paper now, it most likely won't become more popular in the future ;-)

 Links

1. Matthew Effect. Wikipedia
2. Matúš Medo, Giulio Cimini, and Stanislao Gualdi.Temporal Effects in the Growth of Networks. Phys. Rev. Lett. 107, 2011
3. W. Elmenreich. Why is it important to get cited?. Self-Organizing Networked Systems Blog. October 2012
4. Citation averages, 2000-2010, by fields and years. Times Higher Eduction 2011.