Abstract
The goal of engineering self-organising emergent systems is to acquire a macroscopic system behaviour solely from autonomous local activity and interaction. Due to the non-deterministic nature of such systems, it is hard to guarantee that the required macroscopic behaviour is achieved and maintained. Before even considering a self-organising emergent system in an industrial context, e.g. for Automated Guided Vehicle (AGV) transportation systems, such guarantees are needed. An empirical analysis approach is proposed that combines realistic agent-based simulations with existing scientific numerical algorithms for analysing the macroscopic behaviour. The numerical algorithm itself obtains the analysis results on the fly by steering and accelerating the simulation process according to the algorithm’s goal. The approach is feasible, compared to formal proofs, and leads to more reliable and valuable results, compared to mere observation of simulation results. Also, the approach allows to systematically analyse the macroscopic behaviour to acquire macroscopic guarantees and feedback that can be used by an engineering process to iteratively shape a self-organising emergent solution.
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References
Egemin, DistriNet: Emc2: Egemin Modular Controls Concept., (IWT-funded project with participants: Egemin and DistriNet (Started on 1 March 2004), ending on 28 February (2006), http://www.egemin.be (research group of K.U.Leuven)
De Wolf, T., Holvoet, T.: Emergence and Self-Organisation: a statement of similarities and differences. In: Proceedings of the Second International Workshop on Engineering Self-Organising Applications, New York, USA, pp. 96–110 (2004)
Wegner, P.: Why Interaction is More Powerful than Algorithms. Communications of the ACM 40, 80–91 (1997)
Edmonds, B., Bryson, J.J.: The Insufficiency of Formal Design Methods - the necessity of an experimental approach for understanding and control of complex MAS. In: Proceedings of the 3rd Internation Joint Conference on Autonomous Agents and Multi Agent Systems (AAMAS 2004), pp. 938–945. ACM Press, New York (2004)
Edmonds, B.: Using the Experimental Method to Produce Reliable Self-Organised Systems. In: Brueckner, S.A., Di Marzo Serugendo, G., Karageorgos, A., Nagpal, R. (eds.) ESOA 2005. LNCS (LNAI), vol. 3464, pp. 84–99. Springer, Heidelberg (2005), (to appear spring 2005)
Anthony, R.J.: Emergence: A Paradigm for Robust and Scalable Distributed Applications. In: Proceedings of IEEE International Conference on Autonomic Computing (ICAC 2004), New York, pp. 132–139 (2004)
Van Dyke Parunak, H., Savit, R., Riolo, R.L.: Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users’ Guide. In: Sichman, J.S., Conte, R., Gilbert, N. (eds.) MABS 1998. LNCS (LNAI), vol. 1534, pp. 10–25. Springer, Heidelberg (1998)
Wilson, W.: Resolving Discrepancies between Deterministic Population Models and Individual-Based Simulations. American Naturalist 151, 116–134 (1998)
Kevrekidis, I.G., Gear, C.W., Hummer, G.: Equation-free: The computer-assisted analysis of complex, multiscale systems. AIChE Journal 50, 1346–1355 (2004)
Kevrekidis, I.G., Gear, C.W., Hyman, J.M., Kevrekidis, P.G., Runborg, O., Theodoropoulos, C.: Equation-free, coarse-grained multiscale computation: enabling microscopic simulators to perform system-level analysis. Communications in Mathematical Sciences 1, 715–762 (2003) available, at http://www.intlpress.com/CMS/
Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C: The Art of Scientific Computing., 2nd edn. Cambridge University Press, Cambridge (1992)
Guerin, S., Kunkle, D.: Emergence of Constraint in Self-Organizing Systems. NDPLS: Nonlinear Dynamics, Psychology, and Life Sciences 8, 131 (2004)
De Wolf, T., Samaey, G., Holvoet, T., Roose, D.: Decentralised Autonomic Computing: Analysing Self-Organising Emergent Behaviour using Advanced Numerical Methods. In: Proceedings of IEEE International Conference on Autonomic Computing (ICAC 2005), Seattle, USA (2005)(accepted)
Poulton, G., Guo, Y., James, G., Valencia, P., Gerasimov, V., Li, J.: Directed Self-Assembly of 2-Dimensional Mesoblocks using Top-down/Bottom-up Design. In: Brueckner, S.A., Di Marzo Serugendo, G., Karageorgos, A., Nagpal, R. (eds.) ESOA 2005. LNCS (LNAI), vol. 3464, pp. 137–149. Springer, Heidelberg (2005)
Parunak, H.V.D., Brueckner, S.A.: Engineering Swarming Systems. In: Bergenti, F., Gleizes, M.P., Zambonelli, F. (eds.) Methodologies and Software Engineering for Agent Systems. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol. 11. Springer, Heidelberg (2004)
Nagpal, R.: A Catalog of Biologically-inspired Primitives for Engineering Self-Organization. In: Di Marzo Serugendo, G., Karageorgos, A., Rana, O.F., Zambonelli, F. (eds.) ESOA 2003. LNCS (LNAI), vol. 2977, pp. 53–62. Springer, Heidelberg (2004)
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De Wolf, T., Holvoet, T., Samaey, G. (2006). Development of Self-organising Emergent Applications with Simulation-Based Numerical Analysis. In: Brueckner, S.A., Di Marzo Serugendo, G., Hales, D., Zambonelli, F. (eds) Engineering Self-Organising Systems. ESOA 2005. Lecture Notes in Computer Science(), vol 3910. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734697_11
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DOI: https://doi.org/10.1007/11734697_11
Publisher Name: Springer, Berlin, Heidelberg
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