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

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Multi-Agent Based Simulation XVI (MABS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9568))

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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Notes

  1. 1.

    http://ccl.northwestern.edu/netlogo/.

  2. 2.

    http://www.anylogic.com.

  3. 3.

    http://jade.tilab.com.

  4. 4.

    http://tucson.unibo.it.

  5. 5.

    http://alchemist.apice.unibo.it.

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Authors and Affiliations

  1. DISI, Alma Mater Studiorum–Università di Bologna, via Sacchi 3, 47521, Bologna, Italy

    Sara Montagna, Andrea Omicini & Danilo Pianini

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  1. Sara Montagna
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  2. Andrea Omicini
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  3. Danilo Pianini
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Correspondence to Sara Montagna .

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Editors and Affiliations

  1. Capitole, University Toulouse 1, Toulouse Cedex 9, France

    Benoit Gaudou

  2. Escola Politécnica, Universidade de Sao Paulo, São Paulo, Brazil

    Jaime Simão Sichman

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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: Gaudou, B., Sichman, J. (eds) Multi-Agent Based Simulation XVI. MABS 2015. Lecture Notes in Computer Science(), vol 9568. Springer, Cham. https://doi.org/10.1007/978-3-319-31447-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-31447-1_1

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