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Multi-Agent Systems for Power Engineering Applications—Part II: Technologies, Standards, and Tools for Building Multi-agent Systems

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TLDR
The problem of interoperability between different multi-agent systems and proposes how this may be tackled and the various options available are described and recommendations on best practice are made.
Abstract
This is the second part of a two-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part I of this paper examined the potential value of MAS technology to the power industry, described fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications, and presented a comprehensive review of the power engineering applications for which MAS are being investigated. It also defined the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part II of this paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented. Given the significant and growing interest in this field, it is imperative that the power engineering community considers the standards, tools, supporting technologies, and design methodologies available to those wishing to implement a MAS solution for a power engineering problem. This paper describes the various options available and makes recommendations on best practice. It also describes the problem of interoperability between different multi-agent systems and proposes how this may be tackled.

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References
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TL;DR: The design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge, which is aimed at developing techniques and methodology for building large-scale knowledge bases which are sharable and reusable.
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The Gaia Methodology for Agent-Oriented Analysis and Design

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Knowledge Engineering and Management: The CommonKADS Methodology

TL;DR: The CommonKADS methodology, developed over the last decade by an industry-university consortium led by the authors, is used and makes as much use as possible of the new UML notation standard.
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Ontology mapping: the state of the art

TL;DR: Ontology mapping is seen as a solution provider in today's landscape of ontology research as mentioned in this paper and provides a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners.
Proceedings Article

Ontology Mapping: The State of the Art

TL;DR: This article comprehensively reviews and provides insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapped.
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