The study of Multiagent Systems (MASs) focuses on those systems in which many intelligent agents interact with each other. The agents are considered to be autonomous entities which contain intelligence that serves for solving their selfish or common problems, and to achieve certain goals. However, the autonomous, responsive, and proactive natures of agents make the development of agent-based software systems more complex than other software systems. Furthermore, the design and implementation of a MAS may become even more complex and difficult to implement when considering new requirements and interactions for new agent environments like the Semantic Web. We believe that both domain-specific modeling and the use of a domain-specific modeling language (DSML) may provide the required abstraction, and hence support a more fruitful methodology for the development of MASs. In this paper, we first introduce a DSML for MASs with both its syntax and semantics definitions and then show how the language and its graphical tools can be used during model-driven development of real MASs. In addition to the classical viewpoints of a MAS, the proposed DSML includes new viewpoints which specifically support the development of software agents working within the Semantic Web environment. The practical use of the DSML is exemplified with a case study on the development of an agentbased expert finding system.

Autonomous, responsive and proactive nature of agents makes development of agent-based software systems more complex than other software systems. A Domain Specific Modeling Language (DSML) may provide the required abstraction and hence support a more fruitful methodology for the development of MASs especially working on the new challenging environments such as the Semantic Web. In this paper, we introduce a domain specific metamodel for MASs working on the Semantic Web. This new metamodel paves the way for definition of an abstract syntax and a concrete syntax for a future DSML of agent systems. Achieved DSML syntax is supported with a graphical modeling toolkit.

Software agents became popular in the development of complex software systems,especially those requiring autonomous and proactive behavior. Agents interact with each other within a Multi-agent System (MAS), in order to perform certain defined tasks in a collaborative and/or selfish manner. However, the autonomous, proactive and interactive structure of MAS causes difficulties when developing such software systems. It is within this context,that the use of a Domain-specific Language (DSL) may support easier and quicker MAS development methodology. The impact of such DSL usage could beclearer when considering the development of MASs, especially those working on new challenging environments like the Semantic Web. Hence, this paper introduces a new DSL for Semantic Web enabled MASs. This new DSL is called Semantic web Enabled Agent Language (SEA_L). Both the SEA_L user-aspects and the way of implementing SEA_L are discussed in the paper. The practical use of SEA_L is also demonstrated using a case study which considers the modeling of a multi-agent based e-barter system. When considering the language implementation, we first discuss the syntax of SEA_L and we show how the specifications of SEA_L can be utilized during the code generation of real MAS implementations. The syntax of SEA_L is supported by textual modeling toolkits developed with Xtext. Code generation for the instance models are supplied with the Xpand tool

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Internal complexity of agents makes development of agentbased software systems complicated. On the other hand, MAS implementation becomes even more complex when new requirements and interactions for environments such as the Semantic Web is considered. A Domain Specific Modelling Language (DSML) can provide the required abstraction and hence support a more fruitful methodology for the development of MAS especially working on the new challenging environments like the Semantic Web. In this paper, a graphical syntax tool is introduced in which agent developers can model MASs according to a DSML called Semantic web Enabled Agent Modeling Language, SEA_ML.