PanSim+ Sim-2APL: A framework for large-scale distributed simulation with complex agents

Parantapa Bhattacharya, Jan de Mooij, Davide Dell'anna, Mehdi Dastani, Brian Logan, Samarth Swarup

Research output: Contribution to conferencePaperAcademic

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.
Original languageEnglish
Publication statusPublished - 31 Oct 2021

Keywords

  • Distributed Simulation
  • Agent-based Simulation
  • Social Simulation

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  • Quantifying the Effects of Norms on COVID-19 Cases Using an Agent-Based Simulation

    de Mooij, J., Dell'anna, D., Bhattacharya, P., Dastani, M., Logan, B. & Swarup, S., 15 Jan 2022, Multi-Agent-Based Simulation XXII. MABS 2021.. Van Dam, K. H. & Verstaevel, N. (eds.). Springer, p. 99-112 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13128 LNAI).

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