Victor Fernández, Francisco Grimaldo, Miguel Lozano, Juan M. Orduña


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.


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Paper Citation

in Harvard Style

Fernández V., Grimaldo F., Lozano M. and M. Orduña J. (2010). EVALUATING JASON FOR DISTRIBUTED CROWD SIMULATIONS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-674-022-1, pages 206-211. DOI: 10.5220/0002729802060211

in Bibtex Style

author={Victor Fernández and Francisco Grimaldo and Miguel Lozano and Juan M. Orduña},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},

in EndNote Style

JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
SN - 978-989-674-022-1
AU - Fernández V.
AU - Grimaldo F.
AU - Lozano M.
AU - M. Orduña J.
PY - 2010
SP - 206
EP - 211
DO - 10.5220/0002729802060211