Abstract
Agents in open self-organizing systems have to cope with a variety of uncertainties. In order to increase their utility and to ensure stable operation of the overall system, they have to capture and adapt to these uncertainties at runtime. This can be achieved by formulating an expectancy of the behavior of others and the environment. Trust has been proposed as a concept for this purpose.
In this paper, we present trust-based scenarios as an enhancement of current trust models. Trust-based scenarios represent stochastic models that allow agents to take different possible developments of the environment’s or other agents’ behavior into account. We demonstrate that trust-based scenarios significantly improve the agents’ capability to predict future behavior with a distributed power management application.
Chapter PDF
Similar content being viewed by others
Keywords
References
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: Proc. of the Power & Energy Student Summit 2010, pp. 40–42 (October 2010)
Bouffard, F., Galiana, F.: Stochastic security for operations planning with significant wind power generation. In: Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, pp. 1–11. IEEE (2008)
Chang, B., Kuo, S., Liang, Y., Wang, D.: Markov chain-based trust model for analyzing trust value in distributed multicasting mobile ad hoc networks. In: Asia-Pacific Services Computing Conference, pp. 156–161. IEEE (2008)
Densing, M.: Hydro-electric power plant dispatch-planning—multi-stage stochastic programming with time-consistent constraints on risk. Dissertation Abstracts International 68(04) (2007)
Hochreiter, R., Pflug, G.: Financial scenario generation for stochastic multi-stage decision processes as facility location problems. Annals of Operations Research 152(1), 257–272 (2007)
Hussain, F., Chang, E., Dillon, T.: Markov model for modelling and managing dynamic trust. In: 3rd IEEE International Conference on Industrial Informatics, pp. 725–733. IEEE (2005)
Hussain, F., Chang, E., Hussain, O.: A robust methodology for prediction of trust and reputation values. In: Proc. of the 2008 ACM Workshop on Secure Web Services, pp. 97–108. ACM (2008)
Kiefhaber, R., Anders, G., Siefert, F., Ungerer, T., Reif, W.: Confidence as a Means to Assess the Accuracy of Trust Values. In: Proc. of the 11th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications (TrustCom 2012). IEEE (2012)
Li, L., Wang, Y., Varadharajan, V.: Fuzzy regression based trust prediction in service-oriented applications. In: Autonomic and Trusted Computing, pp. 221–235 (2009)
Mayer, R.C., Davis, J.H., Schoorman, F.D.: An integrative model of organizational trust. The Academy of Management Review 20(3), 709–734 (1995)
Pappala, V., Erlich, I.: Power System Optimization under Uncertainties: A PSO Approach. In: Swarm Intelligence Symposium (SIS 2008), pp. 1–8. IEEE (2008)
Ramchurn, S., Huynh, D., Jennings, N.: Trust in multi-agent systems. The Knowledge Engineering Review 19(01), 1–25 (2004)
Sahinidis, N.V.: Optimization under uncertainty: state-of-the-art and opportunities. Computers & Chemical Engineering 28(6-7), 971–983 (2004)
Steghöfer, J.-P., et al.: Trustworthy Organic Computing Systems: Challenges and Perspectives. In: Xie, B., Branke, J., Sadjadi, S.M., Zhang, D., Zhou, X. (eds.) ATC 2010. LNCS, vol. 6407, pp. 62–76. Springer, Heidelberg (2010)
Zhang, B., Luh, P., Litvinov, E., Zheng, T., Zhao, F., Zhao, J., Wang, C.: Electricity auctions with intermittent wind generation. In: Power and Energy Society General Meeting, pp. 1–8. IEEE (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 IFIP International Federation for Information Processing
About this paper
Cite this paper
Anders, G., Siefert, F., Steghöfer, JP., Reif, W. (2014). Trust-Based Scenarios – Predicting Future Agent Behavior in Open Self-organizing Systems. In: Elmenreich, W., Dressler, F., Loreto, V. (eds) Self-Organizing Systems. IWSOS 2013. Lecture Notes in Computer Science, vol 8221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54140-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-54140-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54139-1
Online ISBN: 978-3-642-54140-7
eBook Packages: Computer ScienceComputer Science (R0)