In this paper we introduce a method of partitioning agents onto machines using an adapted k-means clustering algorithm. We present, validate and use an analysis ...

Simulating crowds is a challenging but important problem. There are various methodologies in the literature ranging from.

Ingalls, eds. CLUSTER BASED PARTITIONING FOR AGENT-BASED CROWD SIMULATIONS. Yongwei Wang. Michael Lees. Wentong Cai. Suiping Zhou. Malcolm Yoke Hean Low.

This paper introduces a method of partitioning agents onto machines using an adapted k-means clustering algorithm, and presents, validate and uses an ...

Cluster Based Partitioning for Agent-based Crowd Simulations. 1) Evenly Distribute Virtual. Environment among. Partitions. 2) Perform Grid-based. Clustering ...

Jun 10, 2022 · This paper presents a new partitioning approach for distributed agent-based simulation systems, supporting spatially and non-spatially attached simulations.

The partitioning problem consists of finding a near-optimal partition of regions (containing all the agents in the system) that simultaneously fulfills two ...

Clustering is a technique used to group similar objects or values together; the notion of similarity can be defined in a number of ways. For agent-based crowd ...

Agent-based crowd simulation, which aims to simulate large crowds of autonomous agents with realistic behavior, is a challenging but important problem.

This report investigates how the construction and query time of multiple spatial partitioning data structures is impacted by spatial distribution of and ...