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.

Extending the Gillespie's Stochastic Simulation Algorithm for Integrating Discrete-Event and Multi-Agent Based Simulation

Sara Montagna;
2015

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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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2690183
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