Model driven development of multi-agent systems with repositories of social patterns

  • Authors:
  • Rubén Fuentes-Fernández;Jorge J. Gómez-Sanz;Juan Pavón

  • Affiliations:
  • Universidad Complutense Madrid, Dep. Ingeniería del Software e Inteligencia Artificial, Madrid, Spain;Universidad Complutense Madrid, Dep. Ingeniería del Software e Inteligencia Artificial, Madrid, Spain;Universidad Complutense Madrid, Dep. Ingeniería del Software e Inteligencia Artificial, Madrid, Spain

  • Venue:
  • ESAW'06 Proceedings of the 7th international conference on Engineering societies in the agents world VII
  • Year:
  • 2006

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Abstract

Design patterns are templates of general solutions to commonly-occurring problems in the analysis and design of software systems. In mature development processes, engineers use and combine these patterns to work out those parts of their systems that correspond to well-identified issues in their domains. The design of new structures is just concerned with those aspects that are specific for their projects and with the glue between different components. Model driven development approaches can benefit of design patterns to improve the building of models and their transformations; at the same time, design patterns can take advantage in this kind of approaches of a better integration in the overall development process. In the case of Agent-Oriented Software Engineering, design solutions for agents and multi-agent systems have been also described in the literature. However, their application and transformation to code largely relies on manual processes. This paper proposes a framework that includes repositories of patterns that can be reused in different projects and processes to generate models and code for multi-agent systems on different target platforms. Instead of focusing on low-level issues, our approach positions the abstraction level of these design patterns at the intentional and social features that characterize multi-agent systems. The paper illustrates this framework with a case study about the development of the models of an agent-based system for collaborative filtering of information.