Knowledge Management with Multi-Agent System in BI Systems Integration
Dejan Lavbi · InTech eBooks · 2012
Acceptance 54 high-level unknown contexts from known contexts, to make decisions and to adapt to the environment, current status, and personal setting of the user.The purpose of this chapter is to present integration of several information resources for Decision Support in Enterprises using agent-oriented approach based on ontologies.The goal of our research is to minimize the gap between business users and agents as special type of application systems that perform tasks in their behalf.The intention was to apply BR approach for ontology manipulation in MAS.Ontology used in our Multi-Agent System for Decision Support in Enterprises (DSS-MAS) was divided into task and domain ontologies while business users were enabled to manipulate them directly in a user friendly environment without requirement of detailed technical knowledge.The remainder of this chapter is structured as follows.First we present some background in the following section 2 with emphasis on agents, ontologies and related work with clear definition of the problem and proposal for solution.Next, in section 3, we introduce our case study of integrated Multi-Agent environment from the domain of mobile communications with emphasis on architecture and the roles of agents and ontologies.The case study is focused in one of the mobile operators and furthermore oriented to supply and demand of mobile phones.After presentation of system architecture and decomposition of ontology of every agent from DSS-MAS will be presented in detail.Details of case study implementation will be given in section 4. Finally the last section 5 presents conclusions. Multi-agent systems and ontologiesMulti-Agent Systems (MAS) offer a new dimension for cooperation and coordination in an enterprise.The MAS paradigm provides a suitable architecture for a design and implementation of integrated IS.With agent-based technology a support for complex IS development is introduced by natural decomposition, abstraction and flexibility of management for organisational structure changes (Kishore, Zhang et al. 2006).The MAS consists of a collection of autonomous agents that can define their own goals and actions and can interact and collaborate through communication means.In a MAS environment, agents work collectively to solve specific enterprises' problems.MAS provide an effective platform for coordination and cooperation among multiple functional units in an enterprise.The research on agents and MAS has been on the rise over the last two decades.The stream of research on IS and enterprise integration (Lei, Motta et al. 2002;Kang & Han 2003;Tewari, Youll et al. 2003) makes the MAS paradigm appropriate platform for integrative decision support within IS.Similarities between the agent in the MAS paradigm and the human actor in business organisations in terms of their characteristics and coordination lead us to a conceptualisation where agents in MAS are used to represent actors in human organizations.Today, semantic technologies based on ontologies and inference are considered as a promising means towards the development of the Semantic Web (Davies, Studer et al. 2006).In the field of Computer Science and Information Technology (IT) in general ontology has become popular as a paradigm for knowledge representation in Artificial Intelligence (AI), by providing a methodology for easier development of interoperable and reusable knowledge bases (KB).The most popular definition, from an AI perspective, is given in www.intechopen.com Knowledge Management with Multi-Agent System in BI Systems Integration How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following: