SCoRe: a Self-Organizing Multi-Agent System for Decision Making in Dynamic Software Developement Processes

International audienceSoftware systems are becoming more and more complex. A common dilemma faced by software engineers in building complex systems is the lack of method adaptability. However, existing agent-based methodologies and tools are developed for particular system and are not tailored for new problems. This paper proposes an architecture of a new tool based on SME for self-constructing customized method processes. Our approach is based on two pillars: the process fragment and the MAS meta-model. These two elements are both defined and considered under a specific agent-oriented perspective thus creating a peculiar approach. Our work is based on the self-organization of agents, making it especially suited to deal with highly dynamic systems such as the design of an interactive and adaptive software engineering process

SCoRe: a Self-Organizing Multi-Agent System for Decision Making in Dynamic Software Developement Processes

Software systems are becoming more and more complex. A common dilemma faced by software engineers in building complex systems is the lack of method adaptability. However, existing agent-based methodologies and tools are developed for particular system and are not tailored for new problems. This paper proposes an architecture of a new tool based on SME for self-constructing customized method processes. Our approach is based on two pillars: the process fragment and the MAS meta-model. These two elements are both defined and considered under a specific agent-oriented perspective thus creating a peculiar approach. Our work is based on the self-organization of agents, making it especially suited to deal with highly dynamic systems such as the design of an interactive and adaptive software engineering process

Organization of Multi-Agent Systems: An Overview

In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

A survey of agent-oriented methodologies

This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network