Abstract
In collaborative multi-agent systems, the participating agents have to join forces in order to solve a common goal. The necessary coordination is often realized by message exchange. While this might work perfectly in simulated environments, the implementation of such systems in a field application usually reveals some challenging properties: arbitrary communication networks, message delays due to specific communication technologies, or differing processing speeds of the agents. In this contribution we interpret these properties as sources of variation, and analyze four different multi-agent heuristics with respect to these aspects. In this regard, we distinguish synchronous from asynchronous approaches, and draw conclusions for either type. Our work is motivated by the use case of scheduling distributed energy resources within self-organized virtual power plants.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ferber, J.: Multi-Agent Systems: Introduction to Distributed Artificial Intelligence. Addison-Wesley – An Imprint of Pearson Education (1999)
Shehory, O., Kraus, S.: Methods for task allocation via agent coalition formation. Artificial Intelligence 101(1-2), 165–200 (1998)
Shehory, O., Kraus, S.: Feasible formation of coalitions among autonomous agents in nonsuperadditive environments. Computational Intelligence 15(3), 218–251 (1999)
Griffiths, N., Luck, M.: Coalition formation through motivation and trust. In: Proc. of the 2nd Int. Joint Conf. on Autonomous Agents and Multiagent Systems, pp. 17–24. ACM (2003)
Tröschel, M., Appelrath, H.-J.: Towards reactive scheduling for large-scale virtual power plants. In: Braubach, L., van der Hoek, W., Petta, P., Pokahr, A. (eds.) MATES 2009. LNCS, vol. 5774, pp. 141–152. Springer, Heidelberg (2009)
Nieße, A., Lehnhoff, S., Tröschel, M., Uslar, M., Wissing, C., Appelrath, H.J., Sonnenschein, M.: Market-Based Self-Organized Provision of Active power and Ancillary services: An Agent-Based Approach for Smart Distribution Grids. In: Complexity in Engineering (COMPENG) (2012)
Beer, S., Sonnenschein, M., Appelrath, H.J.: Towards a Self-Organization Mechanism for Agent Associations in Electricity Spot Markets. In: Heiß, H.U., Pepper, P., Schlingloff, H., Schneider, J. (eds.) Informatik 2011 – Proceedings der 41. GI-Jahrestagung. GI-Edition – Lecture Notes in Informatics (LNI), pp. P-191. Bonner Köllen Verlag (2011)
Ashby, W.: Requisite variety and its implications for the control of complex systems. Cybernetica 1(2), 83–99 (1958)
Campbell, A., Riggs, C., Wu, A.S.: On the impact of variation on self-organizing systems. In: Fifth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2011), pp. 119–128. IEEE Computer Society (2011)
Anders, G., Hinrichs, C., Siefert, F., Behrmann, P., Reif, W., Sonnenschein, M.: On the Influence of Inter-Agent Variation on Multi-Agent Algorithms Solving a Dynamic Task Allocation Problem under Uncertainty. In: Sixth IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012), pp. 29–38. IEEE Computer Society (2012)
UCTE: UCTE Operation Handbook – Policy 1: Load-Frequency Control and Performance. Technical Report UCTE OH P1, Union for the Co-ordination of Transmission of Electricity (2009)
Abarrategui, O., Marti, J., Gonzalez, A.: Constructing the active european power grid. The Online Journal on Power and Energy Engineering (OJPEE)Â 1(4) (2010)
Hinrichs, C., Lehnhoff, S., Sonnenschein, M.: A Decentralized Heuristic for Multiple-Choice Combinatorial Optimization Problems. In: Operations Research Proceedings 2012, pp. 297–302. Springer (2014)
Lisovich, M.A., Mulligan, D.K., Wicker, S.B.: Inferring Personal Information from Demand-Response Systems. IEEE Security & Privacy Magazine 8(1), 11–20 (2010)
AlAbdulkarim, L., Lukszo, Z.: Integrating information security requirements in critical infrastructures: smart metering case. International Journal of Critical Infrastructures 6(2), 187–209 (2010)
Chapman, A.C., Rogers, A., Jennings, N.R., Leslie, D.S.: A unifying framework for iterative approximate best-response algorithms for distributed constraint optimization problems. The Knowledge Engineering Review 26(4), 411–444 (2011)
Kok, J.K., Warmer, C.J., Kamphuis, I.G.: Powermatcher: Multiagent control in the electricity infrastructure. In: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems (AAMAS 2005). ACM Press (2005)
Wedde, H.F., Lehnhoff, S., Rehtanz, C., Krause, O.: Bottom-Up Self-Organization of Unpredictable Demand and Supply under Decentralized Power Management. In: 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp. 74–83. IEEE (2008)
Anders, G., Siefert, F., Steghöfer, J.P., Seebach, H., Nafz, F., Reif, W.: Structuring and Controlling Distributed Power Sources by Autonomous Virtual Power Plants. In: IEEE Power and Energy Student Summit (PESS 2010). IEEE Power & Energy Society (2010)
Pournaras, E., Warnier, M., Brazier, F.M.: Local agent-based self-stabilisation in global resource utilisation. International Journal of Autonomic Computing 1(4) (2010)
Li, J., Poulton, G., James, G.: Coordination of Distributed Energy Resource Agents. Applied Artificial Intelligence 24(5), 351–380 (2010)
Horowitz, S.H., Phadke, A.G.: Power System Relaying, 3rd edn. John Wiley & Sons Ltd. (2008)
Geelen, D., van Kempen, G., van Hoogstraten, F., Liotta, A.: A wireless mesh communication protocol for smart-metering. In: 2012 International Conference on Computing, Networking and Communications (ICNC), pp. 343–349. IEEE (2012)
Fischer, M.J., Lynch, N.A., Paterson, M.S.: Impossibility of distributed consensus with one faulty process. Journal of the ACM 32(2), 374–382 (1985)
Nieße, A., Sonnenschein, M.: Using Grid Related Cluster Schedule Resemblance for Energy Rescheduling. In: Donnellan, B., Martins, J.A., Helfert, M., Krempels, K.H. (eds.) SMARTGREENS 2013 – 2nd International Conference on Smart Grids and Green IT Systems, pp. 22–31. INSTICC Press (2013)
Hinrichs, C., Lehnhoff, S., Sonnenschein, M.: Paving the Royal Road for Complex Systems: On the Influence of Memory on Adaptivity. In: Pelster, A., Wunner, G. (eds.) International Symposium Selforganization in Complex Systems: The Past, Present, and Future of Synergetics, Springer (in press)
Han, B., Leblet, J., Simon, G.: Hard Multidimensional Multiple Choice Knapsack Problems, an Empirical Study. Computers & Operations Research 37(1), 172–181 (2010)
Hinrichs, C., Sonnenschein, M., Lehnhoff, S.: Evaluation of a Self-Organizing Heuristic for Interdependent Distributed Search Spaces. In: Filipe, J., Fred, A. (eds.) International Conference on Agents and Artificial Intelligence (ICAART 2013), vol. 1, pp. 25–34. INSTICC Press (2013)
Doval, D., O’Mahony, D.: Overlay Networks: A Scalable Alternative for P2P. IEEE Internet Computing 7(4), 79–82 (2003)
Strogatz, S.: Exploring complex networks. Nature 410(6825), 268–276 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Hinrichs, C., Sonnenschein, M. (2014). The Effects of Variation on Solving a Combinatorial Optimization Problem in Collaborative Multi-Agent Systems. In: Müller, J.P., Weyrich, M., Bazzan, A.L.C. (eds) Multiagent System Technologies. MATES 2014. Lecture Notes in Computer Science(), vol 8732. Springer, Cham. https://doi.org/10.1007/978-3-319-11584-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-11584-9_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11583-2
Online ISBN: 978-3-319-11584-9
eBook Packages: Computer ScienceComputer Science (R0)