A Framework for Validating Task Assignment in Multiagent Systems Using Requirements Importance.
ABSTRACT Multi-agent systems (MASs) are one of the effective approaches for dealing with the recent increase in software complexity and their autonomy. In the MAS research community, there has recently been increasing interest in the adoption of requirements engineering techniques to bridge the gap between the system requirements and the system design. One of the most important tasks based on the requirements description in the MAS design activity is the extraction of roles, which are the fundamental components of multi-agent systems, from it. It is also important to comprehend the relative degree of responsibility of the individual roles. The comprehension helps the developer decide the system architecture and discuss the performance and stability of the system. We introduce the concept of importance as a quantitative metric and an evaluation framework for the extraction of a suitable role set for the system and the task assignment to these roles. The importance is propagated from the requirements to the roles through their assigned tasks. We demonstrate the effectiveness of our framework through a case study and show that our metric and evaluation framework help not only to identify the importance of each role, but also to determine the system architecture.
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ABSTRACT: The purpose of this study is to reduce the difficulties encountered when designing multi-agent systems (MAS). Although MAS are one of the more effective approaches for dealing with the recent increase in software complexity, they are themselves difficult to develop. We believe the difficulties in determining agent responsibilities and the organizational structure as the most significant obstacles to MAS development. In this paper, we propose a design framework for MAS, which includes restriction rules in the goal-oriented requirements description and a generator that transforms the restricted requirements description into a general MAS design model. We demonstrate the effectiveness of our framework through a case study and show how the framework can be used to construct MAS design models more precisely than conventional methods permit.Proceedings of the 2011 ACM Symposium on Applied Computing (SAC), TaiChung, Taiwan, March 21 - 24, 2011; 01/2011