Abstract

In many domains, high-resolution agent-based simulations require experiments with a large number (tens or hundreds of millions) of computationally complex agents. Such large-scale experiments are usually run for efficiency on high-performance computers or clusters, and therefore agent-based simulation frameworks must support parallel distributed computations. The development of experiments with a large number of interconnected agents and a shared environment running in parallel on multiple compute nodes is especially challenging because it introduces the overhead of cross-process communications.
In this paper we discuss the parallel distributed architecture of the farm agent-based simulation framework for social network simulations. To address the issue of shared environment synchronization we used a hybrid approach that distributes the simulation environment across compute nodes and keeps …

Date

September 21, 2025

Authors

Jim Blythe, Alexey Tregubov

Conference

Massively Multi-Agent Systems II: International Workshop, MMAS 2018, Stockholm, Sweden, July 14, 2018, Revised Selected Papers

Pages

96-107

Publisher

Springer International Publishing