DeSim: Distributed Architectures and Concepts for the Simulation of Systems of Systems
The demands on distributed simulation environments is ever increasing. It will become more and more essential to simulate and analyze not the behavior of a single system but that of complex Systems of Systems (SoS).
Traditional methods focus on speeding up the simulation itself (e.g. through parallelization) and mostly lack the capability to execute and especially create and design the models correspondent to these SoS. Consider e.g. a complex value creation chain with existing models for each of its aspects. It might not be desirable to bring all this information together in one system, e.g. because of security/confidentiality concerns of the involved parties.
To tackle this problem, Multi-Agent-Based Simulation (MABS) seems to be a most promising and quickly evolving key concept. It allows for microscopic modelling of actors, their goals, preferences capabilities and interaction between them, which is rather difficult, if not impossible, using traditional physical or cellular models.
Current agent-oriented models, e.g. in the field of traffic simulation, already support interaction, coordination and cooperation models, however, they are very restrictive in that and do not support distributing the models to multiple runtime environments.
The scope of this project comprises finding basic architectures, concepts and requirements for decentral modelling and execution of simulations of SoS.
Based on this, reasonable and suitable methods, models, protocols and utilities from the field of multi-agent systems are to be identified and - if possible - implemented in an existing framework (the Multi-Agent System simulation platform [MASSim], which is used for the annual Multi-Agent Programming Competition) and/or a completely new framework (the Parallel Multi-Agent simulation platform [PMAS]).
Involved Scientists
Prof. Dr. Jürgen Dix

Research Group Computational Intelligence
Department of Informatics
Clausthal University of Technology
Room 116, Am Regenbogen 15, 38678 Clausthal-Zellerfeld
E-Mail: juergen.dix@tu-clausthal.de
Phone: +49 5323 72-7181
Fax: +49 5323 72-7189
Prof. Dr. Jörg Müller

Business Information Technology Unit
Department of Informatics
Clausthal University of Technology
Room 201, Julius-Albert-Straße 4, 38678 Clausthal-Zellerfeld
E-Mail: joerg.mueller@tu-clausthal.de
Phone: +49 5323 72-7141
Fax: +49 5323 72-7199
Publication list
2016
- Tobias Ahlbrecht, Jürgen Dix, Niklas Fiekas, Michael Köster, Philipp Kraus, Jörg P. Müller:
An architecture for scalable simulation of systems of cognitive agents. IJAOSE 5(2/3): 232-265 (2016)
http://www.inderscience.com/info/inarticle.php?artid=80897
- Malte Aschermann, Philipp Kraus, Jörg P. Müller
LightJason: A BDI Framework Inspired by Jason
Technical Report IfI-16-04, Clausthal University of Technology, November 2016.
https://www.in.tu-clausthal.de/fileadmin/homes/techreports/ifi1604aschermann.pdf
An architecture for scalable simulation of systems of cognitive agents. IJAOSE 5(2/3): 232-265 (2016)
http://www.inderscience.com/info/inarticle.php?artid=80897
LightJason: A BDI Framework Inspired by Jason
Technical Report IfI-16-04, Clausthal University of Technology, November 2016.
https://www.in.tu-clausthal.de/fileadmin/homes/techreports/ifi1604aschermann.pdf
2015
- T. Ahlbrecht, J. Dix and F. Schlesinger. From Testing Agent Systems to a Scalable Simulation Platform. In T. Eiter et al. (Eds.): Brewka Festschrift, LNAI 9060, pp. 47-62. Springer International Publishing Switzerland, 2015.
2014
- N. Bulling N and M. Popovici. A game-theoretic approach to compute stable topologies in mobile ad hoc networks. Journal of Logic and Computation, 2014.
- T. Ahlbrecht, J. Dix, M. Köster, P. Kraus and J. P. Müller. A scalable runtime platform for multiagent-based simulation. In F. Dalpiaz et al., editors, Engineering Multiagent Systems II, volume 8758 of Lecture Notes in Artificial Intelligence (LNAI), pages 81-102, Switzerland, 2014. Springer International Publishing.
- N. Bulling N. A survey of multi-agent decision-making. KI 28, 3 (2014), 147–158.
- B. Gernert, S. Schildt, L. Wolf, B. Zeise, P. Fritsche, B. Wagner, M. Fiosins, R. Manesh, J. P. Müller. An interdisciplinary approach to autonomous team-based exploration in disaster scenarios. In Proceedings of 12th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2014). IEEE Press, 2014.
- F. Dalpiaz, J. Dix and B. van Riemsdijk. Eds. Engineering Multi-Agent Systems - Second International Workshop, EMAS 2014, Paris, France, May 5–7, 2014, Revised Selected Papers (2014), vol. 8758 of Lecture Notes in Computer Science, Springer.
2013
- M. Fiosins, J.P. Müller and M. Huhn. A norm-based probabilistic decision-making model for autonomic traffic networks. In J. M. Corchado et al., editors, Highlights on Practical Applications of Agents and Multi-Agent Systems, volume 365 of Communications in Computer and Information Science, pages 49-60. Springer Berlin Heidelberg, 2013.
- J. Fiosina, M. Fiosins and J.P. Müller. Decentralised cooperative agent-based clustering in intelligent traffic clouds. In M. Klusch, M. Paprzycki, and M. Thimm, editors, Multiagent System Technologies: Proceedings of the 11th German Conference on Multiagent System Technologies, volume 8076 of Lecture Notes in Artificial Intelligence (LNAI), pages 59-72. Springer Berlin Heidelberg, 2013.
- J. Fiosina, M. Fiosins and J.P. Müller. Mining the traffic cloud: Data analysis and optimization strategies for cloud-based cooperative mobility management. In J. Casillas et al., editors, Management Intelligent Systems, volume 220 of Advances in Intelligent Systems and Computing, pages 25-32. Springer Berlin Heidelberg, 2013.
- N. Bulling N, M. Dastani and M. Knobbout. Monitoring norm violations in multi-agent systems. In International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 (2013), M. L. Gini, O. Shehory, T. Ito, and C. M. Jonker, Eds., IFAAMAS, pp. 491–498.