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

2015 ◽  
Vol 24 (3) ◽  
pp. 755-795 ◽  
Author(s):  
Moharram Challenger ◽  
Geylani Kardas ◽  
Bedir Tekinerdogan
Keyword(s):  
Systematic Approach ◽  
Modeling Language ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Specific Modeling

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

2014 ◽  
Vol 23 (03) ◽  
pp. 1450005 ◽  
Author(s):  
Sinem Getir ◽  
Moharram Challenger ◽  
Geylani Kardas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Modeling Language ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Definition Of ◽  
Specific Modeling

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_ML's 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_ML's 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_ML's 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_ML's formal semantics. Lessons learned during the development of such a MAS DSML semantics are also reported in this paper.

scholarly journals MASRML - A Domain-specific Modeling Language for Multi-agent Systems Requirements

2020 ◽  
Vol 11 (5) ◽  
pp. 25-45
Author(s):  
Gilleanes Thorwald Araujo Guedes ◽  
Iderli Pereira de Souza Filho ◽  
Lukas Filipe Gaedicke ◽  
Giovane D’Ávila Mendonça ◽  
Rosa Maria Vicari ◽  
...  
Keyword(s):  
Modeling Language ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Systems Requirements ◽  
Specific Modeling

scholarly journals Supporting the platform extensibility for the model-driven development of agent systems by the interoperability between domain-specific modeling languages of multi-agent systems

2017 ◽  
Vol 14 (3) ◽  
pp. 875-912 ◽  
Author(s):  
Geylani Kardas ◽  
Emine Bircan ◽  
Moharram Challenger
Keyword(s):  
Conventional Approach ◽  
Modeling Languages ◽  
Multi Agent Systems ◽  
Model Driven Development ◽  
Agent Systems ◽  
Model Driven ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Specific Modeling

The conventional approach currently followed in the development of domain-specific modeling languages (DSMLs) for multi-agent systems (MASs) requires the definition and implementation of new model-to-model and model-totext transformations from scratch in order to make the DSMLs functional for each different agent execution platforms. In this paper, we present an alternative approach which considers the construction of the interoperability between MAS DSMLs for a more efficient way of platform support extension. The feasibility of using this new interoperability approach instead of the conventional approach is exhibited by discussing and evaluating the model-driven engineering required for the application of both approaches. Use of the approaches is also exemplified with a case study which covers the model-driven development of an agent-based stock exchange system. In comparison to the conventional approach, evaluation results show that the interoperability approach requires both less development time and effort considering design and implementation of all required transformations.

AgentDSM-Eval: A framework for the evaluation of domain-specific modeling languages for multi-agent systems

2021 ◽  
Vol 76 ◽  
pp. 103513
Author(s):  
Omer Faruk Alaca ◽  
Baris Tekin Tezel ◽  
Moharram Challenger ◽  
Miguel Goulão ◽  
Vasco Amaral ◽  
...  
Keyword(s):  
Modeling Languages ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Domain Specific ◽  
Domain Specific Modeling ◽  
Multi Agent ◽  
Specific Modeling

scholarly journals Towards a Domain-Specific Modeling Language for Extracting Event Logs from ERP Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5476
Author(s):  
Ana Pajić Simović ◽  
Slađan Babarogić ◽  
Ognjen Pantelić ◽  
Stefan Krstović
Keyword(s):  
Process Mining ◽  
Modeling Language ◽  
Sufficient Information ◽  
Event Data ◽  
Erp Systems ◽  
Domain Experts ◽  
Domain Specific ◽  
Event Logs ◽  
Domain Specific Modeling ◽  
Specific Modeling

Enterprise resource planning (ERP) systems are often seen as viable sources of data for process mining analysis. To perform most of the existing process mining techniques, it is necessary to obtain a valid event log that is fully compliant with the eXtensible Event Stream (XES) standard. In ERP systems, such event logs are not available as the concept of business activity is missing. Extracting event data from an ERP database is not a trivial task and requires in-depth knowledge of the business processes and underlying data structure. Therefore, domain experts require proper techniques and tools for extracting event data from ERP databases. In this paper, we present the full specification of a domain-specific modeling language for facilitating the extraction of appropriate event data from transactional databases by domain experts. The modeling language has been developed to support complex ambiguous cases when using ERP systems. We demonstrate its applicability using a case study with real data and show that the language includes constructs that enable a domain expert to easily model data of interest in the log extraction step. The language provides sufficient information to extract and transform data from transactional ERP databases to the XES format.

Rule Engines and Agent-Based Systems

2012 ◽  
pp. 211-218 ◽  
Author(s):  
Agostino Poggi ◽  
Michele Tomaiuolo
Keyword(s):  
Dynamic Environments ◽  
Multi Agent Systems ◽  
Rule Engine ◽  
Rule Based ◽  
Agent Based ◽  
Agent Systems ◽  
Loosely Coupled ◽  
Domain Specific ◽  
Multi Agent ◽  
Good Support

Expert systems are successfully applied to a number of domains. Often built on generic rule-based systems, they can also exploit optimized algorithms. On the other side, being based on loosely coupled components and peer to peer infrastructures for asynchronous messaging, multi-agent systems allow code mobility, adaptability, easy of deployment and reconfiguration, thus fitting distributed and dynamic environments. Also, they have good support for domain specific ontologies, an important feature when modelling human experts’ knowledge. The possibility of obtaining the best features of both technologies is concretely demonstrated by the integration of JBoss Rules, a rule engine efficiently implementing the Rete-OO algorithm, into JADE, a FIPA-compliant multi-agent system.

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