Authors:
Victor Fernández
;
Francisco Grimaldo
;
Miguel Lozano
and
Juan M. Orduña
Affiliation:
Universitat de València, Spain
Keyword(s):
Multi-agent architectures, Crowd simulation.
Related
Ontology
Subjects/Areas/Topics:
Agent Platforms and Interoperability
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Programming Environments and Languages
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Large-scale crowd simulations require distributed computer architectures and efficient parallel techniques to achieve the rendering of visually plausible images while simulating the behaviour of crowds of autonomous agents. The Java-based multiagent platforms, devoted to provide the agents with the required lifecycle, represent a key middleware in crowd systems. However, since they are oriented to maximize portability and to reduce the development cost, they may reduce performance and scalability, two important requirements in large-scale crowd simulation systems. This paper studies the performance and scalability provided by Jason, a well known Java-based BDI-MAS platform, as a plausible framework to be used for large-scale crowd simulations. The performance evaluation results show that some improvements should be performed in order to make Jason a suitable middleware for large-scale crowd simulations.