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Agents and Coordination Artifacts for Feature Engineering

  • Alessandro Ricci
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2975)

Abstract

Agents and Multi-Agent Systems (MAS) are considered a suitable paradigm for engineering complex systems. Interaction is a primary source of this complexity and coordination plays a key role for its management, providing the means for modelling and shaping the agent interaction space so as to engineer the global behaviour of the system as a whole. Feature-based systems are certainly complex systems: they are generally composed by several interrelated parts which work together to provide global functionalities. The set of functionalities is not fixed, but typically evolves with the (dynamic) integration of new features. In this paper we investigate the possibility of using agents and coordination abstractions for the engineering of feature-based systems; in particular, typical feature issues – such as feature plug-and-play and the feature-interaction problem – are framed in the agent-based engineering context.

The content of the paper is articulated as follows: First, we provide an overview of agent-oriented software engineering, in particular of the reason why agent paradigm is suitable for complex systems. Here, the importance of the coordination dimension is reminded, in particular the adoption of suitable coordination artifacts to engineer collective behaviour of MAS is discussed. Then, features and feature-based systems are briefly considered, sketching some of the main characteristics which make them complex systems. After that, a perspective for engineering feature-based systems on top of agents and coordination artifacts is provided; the main points of the discussion are exemplified using the TuCSoN MAS coordination model & infrastructure applied to a simple case study typically found in the feature literature, an email service engineering.

Keywords

Multiagent System Tuple Space Engineering Complex System Coordination Artifact Incoming Email 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alessandro Ricci
    • 1
  1. 1.DEISUniversità degli Studi di Bologna a CesenaCesenaItaly

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