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PanSim + Sim-2APL: A Framework for Large-Scale Distributed Simulation with Complex Agents

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Engineering Multi-Agent Systems (EMAS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13190))

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Abstract

Agent-based simulation is increasingly being used to model social phenomena involving large numbers of agents. However, existing agent-based simulation platforms severely limit the kinds of the social phenomena that can modeled, as they do not support large scale simulations involving agents with complex behaviors. In this paper, we present a scalable agent-based simulation framework that supports modeling of complex social phenomena. The framework integrates a new simulation platform that exploits distributed computer architectures, with an extension of a multi-agent programming technology that allows development of complex deliberative agents. To show the scalability of our framework, we briefly describe its application to the development of a model of the spread of COVID-19 involving complex deliberative agents in the US state of Virginia.

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Notes

  1. 1.

    Source code for PanSim is available at https://github.com/parantapa/pansim, and that for Sim-2APL is available at https://bitbucket.org/goldenagents/sim2apl.

  2. 2.

    Here we use the terms simple and complex contagions in their literal sense and not specifically in the sense developed and popularized in [13].

  3. 3.

    https://arrow.apache.org/.

  4. 4.

    https://github.com/toml-lang/toml.

  5. 5.

    To ensure that the socio-psychological module processes and PanSim processes don’t compete for CPU resources we use MPI implementation specific configuration to make PanSim processes sleep during the execution of the socio-psychological module. This configuration trades of some performance for ease of programming.

  6. 6.

    We experimented with using Metis and ParMetis [24] for this partitioning. However, we found that our simple approach was much faster and produced adequately good partitions.

  7. 7.

    Since agents can execute multiple plans during one deliberation cycle, this approach does not restrict the agent’s number of actions per time step.

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Acknowledgments

Parantapa Bhattacharya and Samarth Swarup were supported in part by NSF Expeditions in Computing Grant CCF-1918656 and DTRA subcontract/ARA S-D00189-15-TO-01-UVA.

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Authors and Affiliations

  1. University of Virginia, Charlottesville, VA, 22904, USA

    Parantapa Bhattacharya & Samarth Swarup

  2. Universiteit Utrecht, Utrecht, The Netherlands

    A. Jan de Mooij, Davide Dell’Anna, Mehdi Dastani & Brian Logan

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  1. Parantapa Bhattacharya
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  2. A. Jan de Mooij
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  3. Davide Dell’Anna
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  4. Mehdi Dastani
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Corresponding author

Correspondence to Parantapa Bhattacharya .

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Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Natasha Alechina

  2. University of Turin, Turin, Italy

    Matteo Baldoni

  3. Utrecht University, Utrecht, The Netherlands

    Brian Logan

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Bhattacharya, P., de Mooij, A.J., Dell’Anna, D., Dastani, M., Logan, B., Swarup, S. (2022). PanSim + Sim-2APL: A Framework for Large-Scale Distributed Simulation with Complex Agents. In: Alechina, N., Baldoni, M., Logan, B. (eds) Engineering Multi-Agent Systems. EMAS 2021. Lecture Notes in Computer Science(), vol 13190. Springer, Cham. https://doi.org/10.1007/978-3-030-97457-2_1

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  • DOI: https://doi.org/10.1007/978-3-030-97457-2_1

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