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SAJaS: Enabling JADE-Based Simulations

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Transactions on Computational Collective Intelligence XX

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 9420))

Abstract

Multi-agent systems (MAS) are widely acknowledged as an appropriate modelling paradigm for distributed and decentralized systems, where a (potentially large) number of agents interact in non-trivial ways. Such interactions are often modelled defining high-level interaction protocols. Open MAS typically benefit from a number of infrastructural components that enable agents to discover their peers at run-time. On the other hand, multi-agent-based simulations (MABS) focus on applying MAS to model complex social systems, typically involving a large agent population. Several MAS development frameworks exist, but they are often not appropriate for MABS; and several MABS frameworks exist, albeit sharing little with the former. While open agent-based applications benefit from adopting development and interaction standards, such as those proposed by FIPA, MABS frameworks typically do not support them. In this paper, a proposal to bridge the gap between MAS simulation and development is presented, including two components. The Simple API for JADE-based Simulations (SAJaS) enhances MABS frameworks with JADE-based features. While empowering MABS modellers with modelling concepts offered by JADE, SAJaS also promotes a quicker development of simulation models for JADE programmers. In fact, the same implementation can, with minor changes, be used as a large scale simulation or as a distributed JADE system. In its current version, SAJaS is used in tandem with the Repast simulation framework. The second component of our proposal consists of a MAS Simulation to Development (MASSim2Dev) tool, which allows the automatic conversion of a SAJaS-based simulation into a JADE MAS, and vice-versa. SAJaS provides, for certain kinds of applications, increased simulation performance. Validation tests demonstrate significant performance gains in using SAJaS with Repast when compared with JADE, and show that the usage of MASSim2Dev preserves the original functionality of the system.

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Notes

  1. 1.

    http://www.fipa.org/.

  2. 2.

    This scenario is merely hypothetical; relevant is the variable agent execution order.

  3. 3.

    https://www.eclipse.org/jdt/.

  4. 4.

    We have used a 64 bit Intel Core(TM)2 Duo CPU E8500, 3.16 GHz, 6 GB RAM machine.

  5. 5.

    We point the reader to the JADE documentation for details on these features.

  6. 6.

    The reader can find details about Risk at http://en.wikipedia.org/wiki/Risk_(game).

  7. 7.

    We did not take advantage of these features when collecting results from our experiments, since they are not available in JADE.

  8. 8.

    http://web.fe.up.pt/~hlc/doku.php?id=SAJaS.

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Acknowledgments

The author would like to thank João Lopes for his initial work on SAJaS and MASSim2Dev, and also João Gonçalves and Pedro Costa for providing the source code of their JADE-based Risk game implementation.

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Correspondence to Henrique Lopes Cardoso .

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Cardoso, H.L. (2015). SAJaS: Enabling JADE-Based Simulations. In: Nguyen, N., Kowalczyk, R., Duval, B., van den Herik, J., Loiseau, S., Filipe, J. (eds) Transactions on Computational Collective Intelligence XX . Lecture Notes in Computer Science(), vol 9420. Springer, Cham. https://doi.org/10.1007/978-3-319-27543-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-27543-7_8

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