Abstract
There is an ever increasing number of sources that may be used for knowledge processing. Often this requires dealing with heterogeneous knowledge and current methods become inadequate in these tasks. Thus it becomes important to develop better general methods and tools, or methods tailored to specific problems. In this paper we consider the problem of knowledge integration in a group of social agents. We use approaches based on particle swarm optimization – without the optimization component – to model the diffusion of information in a group of social agents. We present a short description of the theoretical model – a modification of PSO heuristics. We also conduct an experiment comparing this approach to previously researched models of knowledge integration in a group of social agents.
References
Barthelemy, J.P., Janowitz, M.F.: A formal theory of consensus. Siam J. Discrete Math. 4, 305–322 (1991)
Bhat, S.P., Bernstein, D.S.: Finite-time stability of continuous autonomous systems. Siam J. Control Optim. 38(3), 751–766 (2000)
De Montjoye, Y.-A., Stopczynski, A., Shmueli, E., Pentland, A., Lehmann, S.: The strength of the strongest ties in collaborative problem solving. Scientific reports 4, Nature Publishing Group (2014)
Iscaro, G., Nakamiti, G.: A supervisor agent for urban traffic monitoring. In: IEEE International Multi-disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), pp. 167–170. IEEE (2013)
JADE: Java Agent Development Framework. http://jade.tilab.com/
Li, S., Dua, H., Lin, X.: Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics. Automatica 47, 1706–1712 (2011)
Maleszka, M.: Observing collective knowledge state during integration. Expert Syst. Appl. 42(1), 332–340 (2015)
Maleszka, M., Nguyen, N.T., Urbanek, A., Wawrzak-Chodaczek, M.: Building educational and marketing models of diffusion in knowledge and opinion transmission. In: Hwang, D., Jung, J.J., Nguyen, N.-T. (eds.) ICCCI 2014. LNCS (LNAI), vol. 8733, pp. 164–174. Springer, Cham (2014). doi:10.1007/978-3-319-11289-3_17
McMorris, F.R., Powers, R.C.: The median procedure in a formal theory of consensus. Siam J. Discrete Math. 14, 507–516 (1995)
Morzy, M., Kruk, T.: Particle swarm as a model for community formation in social networks. In: Proceedings of Network Intelligence Conference (ENIC) 2016, pp. 40–47. IEEE (2016)
Nagata, T., Sasaki, H.: A multi-agent approach to power system restoration. IEEE Trans. Power Syst. 17(2), 457–462 (2002)
Nguyen, N.T.: Advanced Methods for Inconsistent Knowledge Management. Springer, London (2007)
Nguyen, V.D., Nguyen, N.T.: An influence analysis of the inconsistency degree on the quality of collective knowledge for objective case. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9621, pp. 23–32. Springer, Heidelberg (2016). doi:10.1007/978-3-662-49381-6_3
Peterson, C.K., Newman, A.J., Spall, J.C.: Simulation-based examination of the limits of performance for decentralized multi-agent surveillance and tracking of undersea targets. In: International Society for Optics and Photonics, SPIE Defense+ Security, p. 90910F (2014)
Reynolds, C.W.: Flocks, herds and schools: a distributed behavioral model. ACM SIGGRAPH Comput. Graph. 21(4), 25–34 (1987)
Ren, W., Beard, R.W., Atkins, E.M.: A survey of consensus problems in multi-agent coordination. In: American Control Conference, 2005, Proceedings of the 2005, pp. 1859–1864. IEEE (2005)
Acknowledgment
This research was co-financed by Polish Ministry of Science and Higher Education grant.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Maleszka, M. (2017). Particle Swarm of Agents for Heterogenous Knowledge Integration. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-67074-4_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67073-7
Online ISBN: 978-3-319-67074-4
eBook Packages: Computer ScienceComputer Science (R0)