Abstract
Calculating optimized project plans, consisting of an arbitrary number of activities of different types and within a dynamic available pool of human resources characterized by specific profiles can be a most challenging task. We focus mainly on the project control process based on such project plans, which also provide the possibility to integrate different types of external disturbances that normally influence a project workflow. Observed deviations of precalculated time intervals of activities immediately lead to the activation of the so-called self learning components, which automatically tune the personal parameters of each involved workgroup member. At least there are two processes to observe and to synchronize permanently: Real project workflow (the so-called Real System) and its realtime emulation (the so-called Simulation System). Due to all these dynamic requirements and to gain scalability of the system, the implementation selected is based on the usage of different intelligent software agents.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Brenner, W., Zarnekow, R., Wittig, H.: Intelligent Software Agents, Foundations and Applications. Springer, Heidelberg (1998)
Ferber, J.: Multi-Agent Systems, An Introduction to Distributed Artificial Intelligence. Addison-Wesley Publishing Company, Reading (1999)
http://www.fipa.org (visited 15-12-2004)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company, Reading (1989)
Holm, K.: Die Befragung I, in UNI-TB, Stuttgart (1991)
Kolisch, R., Drexl, A., Sprecher, A.: Neuere Entwicklungen in der Projektplanung. In: Zeitschrift für betriebswirtschaftliche Forschung, Jg. 49 (1997)
Mauerkirchner, M.: Event Based Modelling and Control of Software Processes. In: Engineering of Computer-Based Systems - Proceedings ECBS 1997 Monterey, California (1997)
Mauerkirchner, M.: A General Planning Method for Allocation of Human Resource Groups. In: Moreno-Díaz Jr., R., Buchberger, B., Freire, J.-L. (eds.) EUROCAST 2001. LNCS, vol. 2178, p. 172. Springer, Heidelberg (2001)
Mauerkirchner, M.: Decision Based Adaptive Model for Managing Software Development Projects. In: Kopacek, P., Moreno-Díaz, R., Pichler, F. (eds.) EUROCAST 1999. LNCS, vol. 1798. Springer, Heidelberg (2000)
Pohlheim, H.: Evolutionäre Algorithmen. Springer, Heidelberg (2000)
Rosenbrock, H.H.: An Automatic Method for Finding the Greatest or Least Value of a Function. Computer Journal 4 (1960)
Wooldridge, M., Jennings, N.R.: Intelligent Agents: Theory and Practice. The Knowledge Engineering Review 10(2) (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mauerkirchner, M., Hoefer, G. (2005). Towards Automated Controlling of Human Projectworking Based on Multiagent Systems. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_38
Download citation
DOI: https://doi.org/10.1007/11556985_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29002-5
Online ISBN: 978-3-540-31829-3
eBook Packages: Computer ScienceComputer Science (R0)