Multi-agent Systems Engineering Methodology Research Articles

Analysis and Design by Agent based MaSE Methodology: A Case Study

Multiagent Systems Engineering (MaSE) Methodology is one of old object-oriented methodology which supports the development process and is established based on the development of the object-oriented software engineering methods and their adjustment with the agent view. Some characteristics of the agent like autonomy, creativity and preactivated are not paid attention. The agents are supposed as simple software processes which cooperate to obtain a certain goal. There are two basic phases in MaSE: analysis and design. The analysis phase concentrates on specializing the agent’s roles, their duties and interactions. In design phase, matters such as diagrams and conversations class are introduced. The all steps in MaSE are implemented by graphic tools, agent Tool. This tool (agent Tool) covers all the steps of MaSE methodology design and analysis. In this article, we have covered the MaSE methodology based on a practical experience. The reason of choosing the chain store system is that it has the necessary characteristics like customer and seller autonomic agent technology and it is easier to identify and understand the analysis and design steps.

Use of MaSE methodology for designing a swarm-based multi-agent system

Swarm intelligence is a rapidly growing branch of artificial intelligence with numerous heuristics being developed. These offer faster and more accurate ways to achieve good solutions. Ant colony optimization (ACO) and particle swarm optimization (PSO) are the most common metaheuristics. Based on the behaviour of collectives of ants, birds, fish and others, they offer algorithms which can be used to solve different NP-hard problems. Multi-agent systems (MAS) offer new perspectives on organisation of code into specific components as autonomic, decentralized or distributed agents. The Multi-agent Systems Engineering (MaSE) methodology allows the combination of both aforementioned approaches. This paper presents research based on the AgentSwarm application which evaluates the efficiency of applying MaSE methodology to solve the traveling salesman problem (TSP) using ACO and PSO metaheuristics. Initial results have shown that MaSE is a comprehensive methodology, solid and reliable in building and developing swarm-based multi-agent systems.

MULTIAGENT SYSTEMS ENGINEERING

This paper describes the Multiagent Systems Engineering (MaSE) methodology. MaSE is a general purpose, methodology for developing heterogeneous multiagent systems. MaSE uses a number of graphically based models to describe system goals, behaviors, agent types, and agent communication interfaces. MaSE also provides a way to specify architecture-independent detailed definition of the internal agent design. An example of applying the MaSE methodology is also presented.