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


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Sara Montagna, Andrea Omicini, Danilo Pianini

Benoit Gaudou, Jaime Simão Sichman (eds.)
“Multi-Agent Based Simulation XVI. International Workshop, MABS 2015, Istanbul, Turkey, May 5, 2015, Revised Selected Papers”, chapter 1, pages 3-18
Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence) 9568
Springer
15 March 2016

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

(keywords) ALCHEMIST, Discrete-event simulation, Gillespie algorithm, Multi-agent based simulation, Stochastic simulation

Journals & Series

Events

  • 13th International Workshop on Multi-Agent-Based Simulation (MABS 2015) — 05/05/2015

Publication

— authors

— editors

Benoit Gaudou, Jaime Simão Sichman

— status

published

— sort

paper in proceedings

— publication date

15 March 2016

— volume

Multi-Agent Based Simulation XVI. International Workshop, MABS 2015, Istanbul, Turkey, May 5, 2015, Revised Selected Papers

— series

Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence

— volume

9568

— chapter

1

— pages

3-18

— number of pages

16

URLs

original page

identifiers

— DOI

10.1007/978-3-319-31447-1_1

— IRIS

11585/562458

— Scopus

2-s2.0-84961257364

— print ISSN

0302-9743

— print ISBN

978-3-319-31446-4

— online ISBN

978-3-319-31447-1

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