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2013 Volume 28
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RESEARCH ARTICLE   Open Access    

Model-driven development of multiagent systems: a survey and evaluation

  • International Computer Institute

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  • Abstract: To work in a higher abstraction level is of critical importance for the development of multiagent systems (MAS) since it is almost impossible to observe code-level details of such systems due to their internal complexity, distributedness and openness. As one of the promising software development approaches, model-driven development (MDD) aims to change the focus of software development from code to models. This paradigm shift, introduced by the MDD, may also provide the desired abstraction level during the development of MASs. For this reason, MDD of autonomous agents and MASs has been recognized and become one of the research topics in agent-oriented software engineering (AOSE) area. Contributions are mainly based on the model-driven architecture (MDA), which is the most famous and in-use realization of MDD. Within this direction, AOSE researchers define MAS metamodels in various abstraction levels and apply model transformations between the instances of these metamodels in order to provide rapid and efficient implementation of the MASs in various platforms. Reorganization of the existing MAS development methodologies to support model-driven agent development is another emerging research track. In this paper, we give a state of the art survey on above mentioned model-driven MAS development research activities and evaluate the introduced approaches according to five quality criteria we define on model-driven MAS engineering: (1) definition of a platform independent MAS metamodel, (2) model-to-model transformability, (3) model-to-code transformability, (4) support for multiple MAS platforms and finally (5) tool support for software modeling and code generation. Our evaluation has shown that the researchers contributed to the area by providing MDD processes in which design of the MASs are realized at a very high abstraction level and the software for these MASs are developed as a result of the application of a series of model transformations. However, most of the approaches are incapable of supporting multiple MAS environments due to the restricted specifications of their metamodels and model transformations. Also efficiency and practicability of the proposed methodologies are under debate since the amount and quality of the executable MAS components, gained automatically, appear to be not sufficient.
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  • Cite this article

    Geylani Kardas. 2013. Model-driven development of multiagent systems: a survey and evaluation. The Knowledge Engineering Review 28(4)479−503, doi: 10.1017/S0269888913000088
    Geylani Kardas. 2013. Model-driven development of multiagent systems: a survey and evaluation. The Knowledge Engineering Review 28(4)479−503, doi: 10.1017/S0269888913000088
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RESEARCH ARTICLE   Open Access    

Model-driven development of multiagent systems: a survey and evaluation

  • International Computer Institute

  • Published online: 19 April 2013
The Knowledge Engineering Review  28,  2013, 28(4): 479−503  |  Cite this article

Abstract: Abstract: To work in a higher abstraction level is of critical importance for the development of multiagent systems (MAS) since it is almost impossible to observe code-level details of such systems due to their internal complexity, distributedness and openness. As one of the promising software development approaches, model-driven development (MDD) aims to change the focus of software development from code to models. This paradigm shift, introduced by the MDD, may also provide the desired abstraction level during the development of MASs. For this reason, MDD of autonomous agents and MASs has been recognized and become one of the research topics in agent-oriented software engineering (AOSE) area. Contributions are mainly based on the model-driven architecture (MDA), which is the most famous and in-use realization of MDD. Within this direction, AOSE researchers define MAS metamodels in various abstraction levels and apply model transformations between the instances of these metamodels in order to provide rapid and efficient implementation of the MASs in various platforms. Reorganization of the existing MAS development methodologies to support model-driven agent development is another emerging research track. In this paper, we give a state of the art survey on above mentioned model-driven MAS development research activities and evaluate the introduced approaches according to five quality criteria we define on model-driven MAS engineering: (1) definition of a platform independent MAS metamodel, (2) model-to-model transformability, (3) model-to-code transformability, (4) support for multiple MAS platforms and finally (5) tool support for software modeling and code generation. Our evaluation has shown that the researchers contributed to the area by providing MDD processes in which design of the MASs are realized at a very high abstraction level and the software for these MASs are developed as a result of the application of a series of model transformations. However, most of the approaches are incapable of supporting multiple MAS environments due to the restricted specifications of their metamodels and model transformations. Also efficiency and practicability of the proposed methodologies are under debate since the amount and quality of the executable MAS components, gained automatically, appear to be not sufficient.

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    • This work is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) Electric, Electronic and Informatics Research Group (EEEAG) under grant 109E125. The author also wishes to thank the anonymous reviewers for their accurate comments on the previous versions of the paper. He was able to improve both his work and the paper significantly by taking their critical comments into account.

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    Geylani Kardas. 2013. Model-driven development of multiagent systems: a survey and evaluation. The Knowledge Engineering Review 28(4)479−503, doi: 10.1017/S0269888913000088
    Geylani Kardas. 2013. Model-driven development of multiagent systems: a survey and evaluation. The Knowledge Engineering Review 28(4)479−503, doi: 10.1017/S0269888913000088
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