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From agent interaction protocols to executable code: a model-driven approach

Published: 10 May 2009 Publication History

Abstract

In this paper, we demonstrate how to design protocols with the platform independent modeling language for multiagent systems (Dsml4mas) and discuss a model-driven approach to use protocol descriptions as a base for generating the corresponding agent behaviors which can finally be executed with Jack Intelligent Agents.

References

[1]
C. Hahn. A domain specific modeling language for multiagent systems. In L. Padgham, C. P. Parkes, J. Mueller, and S. Parsons, editors, Proceedings of 7th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2008), pages 233--240, 2008.
[2]
C. Hahn, C. Madrigal-Mora, and K. Fischer. A platform-independent metamodel for multiagent systems. International Journal on Autonomous Agents and Multi-Agent Systems, 18(2):239--266, 2008.
[3]
S. Warwas and C. Hahn. The contrete syntax of the platform independent modeling language for multiagent systems. In Proceedings of the Agent-based Technologies and applications for enterprise interOPerability (ATOP 2008) at AAMAS 2008, 2008.

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Information & Contributors

Information

Published In

cover image Guide Proceedings
AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
May 2009
730 pages
ISBN:9780981738178

Sponsors

  • Drexel University
  • Wiley-Blackwell
  • Microsoft Research: Microsoft Research
  • Whitestein Technologies
  • European Office of Aerospace Research and Development, Air Force Office of Scientific Research, United States Air Force Research Laboratory
  • The Foundation for Intelligent Physical Agents

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 10 May 2009

Author Tags

  1. agent interaction protocols
  2. model transformation
  3. model-driven code generation

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  • Research-article

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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