Moharram Challenger

On the use of a domain-specific modeling language in the development of multiagent systems

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 called SEA_ML 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 methodology proposed for the MAS development based on SEA_ML is also discussed including its example application on the development of an agent-based stock exchange system.

A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems

Multi-agent systems (MASs) include multiple interacting agents within an environment to provide a solution for complex systems that cannot be easily solved with individual agents or monolithic systems. However, the development of MASs is not trivial due to the various agent properties such as autonomy, responsiveness, and proactiveness, and the need for realization of the many different agent interactions. To support the development of MASs various domain-specific modeling languages (DSMLs) have been introduced that provide a declarative approach for modeling and supporting the generation of agent-based systems. To be effective, the proposed DSMLs need to meet the various stakeholder concerns and the related quality criteria for the corresponding MASs. Unfortunately, very often the evaluation of the DSML is completely missing or has been carried out in idiosyncratic approach. If the DSMLs are not well defined, then implicitly this will have an impact on the quality of the MASs. In this paper, we present an evaluation framework and systematic approach for assessing existing or newly defined DSMLs for MASs. The evaluation is specific for MAS DSMLs and targets both the language and the corresponding tools. To illustrate the evaluation approach, we first present SEA_ML, which is a model-driven MAS DSML for supporting the modeling and generation of agent-based systems. The evaluation of SEA_ML is based on a multi-case study research approach and provides both qualitative evaluation and quantitative analysis. We report on the lessons learned considering the adoption of the evaluation approach as well as the SEA_ML for supporting the generation of agent-based systems.

The Formal Semantics of a Domain-Specific Modeling Language for Semantic Web Enabled Multi-Agent Systems

Development of agent systems is without question a complex task when autonomous, reactive and proactive characteristics of agents are considered. Furthermore, internal agent behavior model and interaction within the agent organizations become even more complex and hard to implement when new requirements and interactions for new agent environments such as the Semantic Web are taken into account. We believe that the use of both domain specific modeling and a Domain-specific Modeling Language (DSML) may provide the required abstraction and support a more fruitful methodology for the development of Multi-agent Systems (MASs) especially when they are working on the Semantic Web environment. Although syntax definition based on a metamodel is an essential part of a modeling language, an additional and required part would be the determination and implementation of DSML constraints that constitute the (formal) semantics which cannot be defined solely with a metamodel. Hence, in this paper, formal semantics of a MAS DSML called Semantic Web enabled Multi-agent Systems (SEA_ML) is introduced. SEA_ML is a modeling language for agent systems that specifically takes into account the interactions of semantic web agents with semantic web services. What is more, SEA_ML also supports the modeling of semantic agents from their internals to MAS perspective. Based on the defined abstract and concrete syntax definitions, we first give the formal representation of SEA_MLs semantics and then discuss its use on MAS validation. In order to define and implement semantics of SEA_ML, we employ Alloy language which is declarative and has a strong description capability originating from both relational and first-order logic in order to easily define complex structures and behaviors of these systems. Differentiating from similar contributions of other researchers on formal semantics definition for MAS development languages, SEA_MLs semantics, presented in this paper, defines both static and dynamic aspects of the interaction between software agents and semantic web services, in addition to the definition of the semantics already required for agent internals and MAS communication. Implementation with Alloy makes definition of SEA_MLs semantics to include relations and sets with a simple notation for MAS model definitions. We discuss how the automatic analysis and hence checking of SEA_ML models can be realized with the defined semantics. Design of an agent-based electronic barter system is exemplified in order to give some flavor of the use of SEA_MLs formal semantics. Lessons learned during the development of such a MAS DSML semantics are also reported in this paper.

A Domain Specific Metamodel for Semantic Web Enabled Multi-Agent Systems

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.

Declarative specifications for the development of multi-agent systems

The designing and implementation of a multi-agent system (MAS), where autonomous agents collaborate with other agents for solving problems, constitute complex tasks that may become even harder when agents work in new interactive environments such as the Semantic Web. In order to deal with the complexities of designing and implementing a MAS, a domain-specific language (DSL) can be employed inside the MASs development cycle. In such a manner, a MAS can be completely specified by programs written in a DSL. Such programs are declarative, expressive, and at the right abstraction level. In this way the complexity of MAS development is then partially shifted to DSL development and the task herein can be much more feasible by using a proper DSL development methodology and related tools. This paper presents and discusses our methodology for DSL development based on declarative formal specifications that are easy to compose, and its usage during MAS development. A practical case-study is also provided covering an example of a MASs development for expert finding systems. By using denotational semantics for precisely defining the language, we show that it is possible to generate the language automatically. In addition, using attribute grammars makes it possible to have modular methodology within which evolutionary language development becomes easier. A multi-agent system development language based on declarative specificationsLanguage is defined formally via denotational semantics and attribute grammars.Applying denotational semantics provided precise definitions of the language.We could generate the language automatically from formal semantics.Using attribute grammars made evolutionary language development easier.

Design and implementation of a multiagent stock trading system

Stock trading is one of the key items in an economy and estimating its behavior and taking the best decision in it are among the most challenging issues. Solutions based on intelligent agent systems are proposed to cope with those challenges. Agents in a multiagent system (MAS) can share a common goal or they can pursue their own interests. That nature of MASs exactly fits the requirements of a free market economy. Although existing studies include noteworthy proposals on agent‐based market simulation and researchers discuss theoretical design issues of agent‐based stock exchange systems, unfortunately only a very few of the studies consider exact development and implementation of multiagent stock trading systems within the software engineering perspective and guides to the software engineers for constructing such software systems starting from scratch. To fill this gap, in this paper, we discuss the development of a multiagent‐based stock trading system by taking into consideration software design according to a well‐defined agent oriented software engineering methodology and implementation with a widely‐used MAS software development framework. Each participant in the system is first designed as belief–desire–intention agents with their facts, goals, and plans, and then belief–desire–intention reasoning and behavioral structure of the designed agents are implemented. Lessons learned during design and development within the software engineering perspective and evaluation of the implemented multiagent stock exchange system are also reported. Copyright

Development of an agent based e-barter system

A barter system is an alternative commerce approach where customers meet at a marketplace in order to exchange their goods or services without currency. In order to cope with challenges of electronic barter systems (e.g. efficient management of trades and determination of best-matching goods and their suppliers), several software systems based on intelligent agents have been proposed. However only a very few of these proposals consider exact development and implementation of multi-agent e-barter systems. Besides, most of the approaches consider matching between exchanged goods in which only price and quantity information are used. Hence, in this paper, we discuss design and implementation of a multi-agent e-barter system which utilizes ontology-based comparison for bid matching. Formal representation and decision-making criteria for agent mediated barter process are given and behavioral model of collaborating agents within the system is described. In addition to the traditional e-barter members, a new type of software agent is introduced in order to infer about semantic closeness between offered and purchased items. Related approach may enhance capabilities of e-barter systems in the way of finding the most appropriate matches between supplies and demands, considering not only price and quantities for goods.

Towards a DSML for semantic web enabled multi-agent systems

Software agents are considered as autonomous software components which are capable of acting to meet its design objectives. To perform their tasks and interact with each other, agents constitute systems called Multi-agent systems (MAS). Although agent researchers have a great effort in MAS metamodeling and model-driven MAS development, a significant deficiency exists in current studies when we consider providing a complete Domain Specific Modeling Language (DSML) for MASs. We believe that a DSML increases the descriptive power of a MAS metamodel, defines the system semantics and hence supports 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 new DSML for MASs with its abstract syntax, the textual concrete syntax and the interpreter mechanism. The practical use of the DSML is illustrated with a case study which considers the modeling of a multi-agent based e-barter system.

DSML4CP: A Domain-specific Modeling Language for Concurrent Programming

Abstract Nowadays, concurrent programs are an inevitable part of many software applications. They can increase the computation performance of the applications by parallelizing their computations. One of the approaches to realize the concurrency is using multi thread programming. However, these systems are structurally complex considering the control of the parallelism (such as thread synchronization and resource control) and also considering the interaction between their components. So, the design of these systems can be difficult and their implementation can be error-prone especially when the addressed system is big and complex. On the other hand, a Domain-specific Modeling Language (DSML) is one of the Model Driven Development (MDD) approaches which tackles this problem. Since DSMLs provide a higher abstraction level, they can lead to reduce the complexities of the concurrent programs. With increasing the abstraction level and generating the artifacts automatically, the performance of developing the software (both in design and implementation phases) is increased, and the efficiency is raised by reducing the probability of occurring errors. Thus, in this paper, a DSML is proposed for concurrent programs, called DSML4CP, to work in a higher level of abstraction than code level. To this end, the concepts of concurrent programs and their relationships are presented in a metamodel. The proposed metamodel provides a context for defining abstract syntax, and concrete syntax of the DSML4CP. This new language is supported by a graphical modeling tool which can visualize different instance models for domain problems. In order to clarify the expressions of the language; the static semantic controls are realized in the form of constraints. Finally, the architectural code generation is fulfilled via model transformation rules using the templates of the concurrent programs. To increase level of the DSML׳s leverage and to demonstrate the general support of concurrent programming by the DSML, the transformation mechanism of the tool supports two well-known and highly used programming languages for code generation; Java and C#. The performed experiments on two case studies indicate a high performance for proposed language. In this regard, the results show automatic generation of 79% of the final code and 86% of the functions/modules on average.

A Hybrid Distributed Mutual Exclusion Algorithm for Cluster-Based Systems

Distributed mutual exclusion is a fundamental problem which arises in various systems such as grid computing, mobile ad hoc networks (MANETs), and distributed databases. Reducing key metrics like message count per any critical section (CS) and delay between two CS entrances, which is known as synchronization delay, is a great challenge for this problem. Various algorithms use either permission-based or token-based protocols. Token-based algorithms offer better communication costs and synchronization delay. Raymonds and Suzuki-Kasamis algorithms are well-known token-based ones. Raymonds algorithm needs only O(log2()) messages per CS and Suzuki-Kasamis algorithm needs just one message delivery time between two CS entrances. Nevertheless, both algorithms are weak in the other metric, synchronization delay and message complexity correspondingly. In this work, a new hybrid algorithm is proposed which gains from powerful aspects of both algorithms. Raysuzs algorithm (the proposed algorithm) uses a clustered graph and executes Suzuki-Kasamis algorithm intraclusters and Raymonds algorithm interclusters. This leads to have better message complexity than that of pure Suzuki-Kasamis algorithm and better synchronization delay than that of pure Raymonds algorithm, resulting in an overall efficient DMX algorithm pure algorithm.