An Ontology-Driven Framework for Deploying JADE Agent Systems

Nyulas, Csongor; O’Connor, Martin J.; Tu, Samson W.; Buckeridge, David L.; Okhmatovskaia, Anna; Musen, Mark A.

doi:10.1109/wiiat.2008.25

Cited by 17 publications

(12 citation statements)

References 14 publications

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“…For instance, Girardi and Leite (2008) address explicitly the model of the MAS domain. Nyulas et al (2008) present an ontology-driven framework for deploying MAS upon JADE (Bellifemine et al 2007). Sensoy et al (2010) and Fornara and Colombetti (2009) use OWL ontologies to define the policies that rule agent behaviour.…”

Section: Ontology-driven Mas and Soa Developmentmentioning

confidence: 99%

Ontology in Software Engineering

Pileggi¹,

Lopez-Lorca²,

Beydoun³

2018

Australasian Conference on Information Systems 2018

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During the past years, ontological thinking and design have become more and more popular in the field of Artificial Intelligence (AI). More recently, Software Engineering (SE) has evolved towards more conceptual approaches based on the extensive adoption of models and meta-models. This paper briefly discusses the role of ontologies in SE according to a perspective that closely matches the theoretical life-cycle. These roles vary considerably across the development lifecycle. The use of ontologies to improve SE development activities is still relatively new (2000 onward), but it is definitely no more a novelty. Indeed, the role of such structures is well consolidated in certain SE aspects, such as requirement engineering. On the other hand, despite their well-known potential as knowledge representation mechanisms, ontologies are not completely exploited in the area of SE. We first (i) proposes a brief overview of ontologies and their current understanding within the Semantic Web with a focus on the benefits provided; then, the role that ontologies play in the more specific context of SE is addressed (ii); finally, we deal with (iii) some brief considerations looking at specific types of software architecture, such as Multi-Agent Systems (MAS) and Service-Oriented Architecture (SOA). The main limitation of our research is that we are focusing on traditional developments, where phases occur mostly sequentially. However, industry has fully embraced agile developments. It is unclear that agile practitioners are willing to adopt ontologies as a tool, unless we ensure that they can provide a clear benefit and they be used in a lean way, without introducing significant overhead to the agile development process.

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Section: Ontology-driven Mas and Soa Developmentmentioning

confidence: 99%

Ontology in Software Engineering

Pileggi¹,

Lopez-Lorca²,

Beydoun³

2018

Australasian Conference on Information Systems 2018

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“…From a technical perspective, given that the proposed multiagent system relies on semantic resources, a notable work is the BioSTORM system [78]. BioS-TORM elaborated on ontology-based, end-to-end deployment of JADE-based agent systems by exploiting diverse surveillance methods.…”

Section: Related Workmentioning

confidence: 99%

“…In terms of development, we find the potential to assess whether BioSTORM could be applicable in the particular application domain interesting [78]. In addition, in the current implementation, the Signal Detection Agents are handling the R output of the respective detection methods.…”

Section: Challenges and Future Workmentioning

confidence: 99%

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Koutkias

Jaulent

2015

J Med Syst

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Pharmacovigilance is the scientific discipline that copes with the continuous assessment of the safety profile of marketed drugs. This assessment relies on diverse data sources, which are routinely analysed to identify the so-called "signals", i.e. potential associations between drugs and adverse effects, that are unknown or incompletely documented. Various computational methods have been proposed to support domain experts in signal detection. However, recent comparative studies illustrated that current methods exhibit high false-positive rates, significantly variable performance across different datasets used for analysis and events of interest, but also complementarity in their outcomes. In this regard, in order to reinforce accurate and timely signal detection, we elaborated through an agent-based approach towards systematic, joint exploitation of multiple heterogeneous signal detection methods, data sources and other drug-related resources under a common, integrated framework. The approach relies on a multiagent system operating based on a collaborative agent interaction protocol, aiming to implement a comprehensive workflow that comprises of method selection and execution, as well as outcomes' aggregation, filtering, ranking and annotation. This paper presents the design of the proposed multiagent system, discusses implementation issues and demonstrates the applicability of the proposed solution in an example signal detection scenario. This work constitutes a step towards large-scale, integrated and knowledge-intensive computational signal detection.

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“…For example, by designing a reusable ontology allowing complex queries on the domain of "MAS development" in [7] Girardi and her colleagues propose an ontology-based multi-agent development process that can model all the phases of development of MAS. As another example, Nyulas et al present in [12] an architecture to develop and deploy end-to-end solutions for MAS. They focus on the deployment steps of the system.…”

Section: Related Workmentioning

confidence: 99%

Ontology-mediated Validation of Software Models

Lopez-Lorca

Beydoun

Sterling

et al. 2011

Information Systems Development

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When errors in software modelling activities propagate to later phases of software development lifecycle, they become costlier to fix and lower the qual-ity of the final product. Early validation of software models can prevent rework and incorrect development non-compliant with client's specification. In this paper we advocate the use of ontologies to validate and improve the quality of software models as they are being developed, at the same time bridging the traditional gap between developers and clients. We propose a general ontology-mediated process to validate software models that can be adapted in a broad range of software development projects. We illustrate this for Multi-Agent Systems (MAS) develop-ment providing early evidence of the soundness of our approach. We successfully validate and improve the quality of MAS models for a reallife development pro-ject, illustrating the ontology-mediated models validation in a commercial setting. Disciplines Physical Sciences and Mathematics Publication DetailsLopez-Lorca, A., Beydoun, G., Sterling, L. & Miller, T. (2011 Abstract When errors in software modelling activities propagate to later phases of software development lifecycle, they become costlier to fix and lower the quality of the final product. Early validation of software models can prevent rework and incorrect development non-compliant with client's specification. In this paper we advocate the use of ontologies to validate and improve the quality of software models as they are being developed, at the same time bridging the traditional gap between developers and clients. We propose a general ontology-mediated process to validate software models that can be adapted in a broad range of software development projects. We illustrate this for Multi-Agent Systems (MAS) development providing early evidence of the soundness of our approach. We successfully validate and improve the quality of MAS models for a real-life development project, illustrating the ontology-mediated models validation in a commercial setting.

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An Ontology-Driven Framework for Deploying JADE Agent Systems

Cited by 17 publications

References 14 publications

Ontology in Software Engineering

Ontology in Software Engineering

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Ontology-mediated Validation of Software Models

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