Extending the gillespie’s stochastic simulation algorithm for integrating discrete-event and multi-agent based simulation

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Abstract

Whereas Multi-Agent Based Simulation (MABS) is emerging as a reference approach for complex system simulation, the event-driven approach of Discrete-Event Simulation (DES) is the most used approach in the simulation mainstream. In this paper we elaborate on two intuitions: (i) event-based systems and multi-agent systems are amenable of a coherent interpretation within a unique conceptual framework; (ii) integrating MABS and DES can lead to a more expressive and powerful simulation framework. Accordingly, we propose a computational model integrating DES and MABS based on an extension of the Gillespie’s stochastic simulation algorithm. Then we discuss a case of a simulation platform (ALCHEMIST) specifically targeted at such a kind of complex models, and show an example of urban crowd steering simulation.

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Montagna, S., Omicini, A., & Pianini, D. (2016). Extending the gillespie’s stochastic simulation algorithm for integrating discrete-event and multi-agent based simulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9568, pp. 3–18). Springer Verlag. https://doi.org/10.1007/978-3-319-31447-1_1

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