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... Ontologies offer significant benefits to multi-agent systems: interoperability, reusability, support for multi-agent system (MAS) development activities (such as system analysis and agent knowledge modeling) and support for MAS operation (such as agent communication and reasoning). [13] There are many scholars at home and abroad have already developed a large architecture of MAS that integrated ontology, Dejan Lavbic [14], proposed a model of ontology to make agents able to reason about unstructured information found on the Web and information available in several internal data sources, Espinasse et al., [15] conducted an interesting research on the collection and extraction of relevant information on the Web from software agents and ontologies. However, there are few theories as a guidance of methodology for ontology based MAS development. ...
Performance of competitive intelligence needs network expert which is composed by various profiles and skills to analyze and evaluate information collected from internal or external sources. Unfortunately, different studies reveal that is difficult for a network; human expert disposes a limited time to acquire and process a huge quantity of information. The core idea of our research paper is to develop an intelligent approach based on ontology and multi-agent system to provide a platform able to analyze and treat information as a network human expert and produce new knowledge useful for decision making based on SWOT analysis method.
... There are involving steps as shown in Figure 1 before designing the conceptual architecture of agent-based KMS. Agent-based KM for higher education [22] Impact of web-2.0/3.0 for agent usability in KM 2014 [19] Agent-based KM for urban social space [4] Collaborative agent-based knowledge discovery [20] Multi-agent KM [23] Multi-agent KM [24] Multi-agent KM for education [21] Multi-agent KM for e-health 2013 [25] Agent roles in personal KM process [26] Agent-based KM for Marketing-Mix Decision Making [27] Multi-agent enterprise KM system (EKMS) [9] Multi-agent enterprise KM system (EKMS) [28] Multi-agent KM for R&D Enterprises 2012 [29] Agent-based KM for academic research [30] Agent-based KM for Collaborative Software Maintenance [31] Agent-based KM for education [32] Multi-agent enterprise KM system (EKMS) [33] Multi-agent enterprise KM system (EKMS) [34] Multi-agent KM [35] Multi-agent KM [36] Multi-agent KM for BI [37] Multi-agent on Personal KM [38] Multi-agent Ontology-based KM According to Figure 2, agent technology on Enterprise KMS (EKMS) received the highest attention from researchers. The reason is about complexity of the EKMS. ...
Green Software Development (GSD) is about adopting green practices in Software Development Life Cycle towards developing environmentally-friendly software products. GSD is knowledge-intensive project, which is heavily depending on sharing of green practices in Community of Practice (CoP) to develop greener software products. As knowledge sharing is an important activity in Knowledge Management (KM), this is how the power of KM comes in to support GSD. However, there is a lack of KM application in
managing green knowledge of GSD. To address the research gap, this paper suggests an implementation of agent technology together with KM application in helping CoP to share
knowledge of GSD. Based on Literature Review, a conceptual architecture of agent-based KM System (KMS) is proposed, with the aim of studying on how multi-agent system and KMS are working together efficiently to enhance knowledge sharing in GSD environment.
... It is believed that, for the business intelligence (BI) of an enterprise, only about 20% of information can be extracted from formatted data stored in relational database. The remaining 80% of information is hidden in unstructured or semi-structured documents [5]. But relevant information gathering in the web is a very complex task. ...
... In (Dejan Lavbic. 2012) [5] author propose an approach in integration of unstructured information found in the web with information available in several internal data sources. In (Maizura, Rosmayati. ...
This article reports a development of a strategic scanning system network prototype system based on multi agent
system and ontology, called Agent-SSSN, for developing business intelligent strategies. This is a cooperative
approach to integrate the knowledge of experts in business intelligent system. The approach presented in this
chapter is targeted towards using ontologies. The use of ontologies in MAS environment enables agent to share
a common set of concept about context, expert user profiles and other domain elements while interacting with
each other. In this paper, we focus especially on the modeling of the system Multi-Agents using O-MaSE
(Organization-based Multiagent Systems Engineering Methodology) and a conceptual diagram of the ontology
database.
In this paper, a content-based video retrieval (CBVR) system called Bounded Coordinate of Motion Histogram version 2 (BCMH v2) was processed on a distributed computing platform by using Apache Hadoop framework and a real-time distributed storage system using HBase. In fact, the amount of multimedia data is growing exponentially. Most of this data is available in image and video models. Analyzing huge data involves complex algorithms, which leads to challenges in optimizing processing time and data storage capacity. Many content-based video retrieval systems are suitable for processing large video dataset, but they are limited by the computational time and/or storage on a single machine. Thus, this paper presents the effectiveness of the proposed method with the distributed computing platform and its evaluation on the HOLLYWOOD2 video dataset. The experimental results demonstrate the good performances of the proposed approach.
Multi-Agents System (MAS) and Ontology are two technologies capable of creating intelligent reasoning and inferring new knowledge useful for decision making. In this paper we propose a platform model called Agent-SSSN whose agents reason as a human actor and collaborate with them to create a Collective Intelligence in Economic Intelligence (EI) coordinated network monitoring. To organize the knowledge in Agent-SSSN and facilitate the reasoning ability of the agent, an ontology-based approach called Onto-Agent-SSSN is presented in this paper.
The dynamics of changes in an organization's environment and the increasing competitiveness of the global knowledge-based economy compel business companies to use their resources efficiently and effectively. Business management theory offers the process-centric approach founded on a systemic perspective of the organizational structure. Within management science, the process-centered approach (which support knowledge productivity and which facilitate innovation) originates in relates to a shift in the way we perceive the organizational structure, i.e. a move away from a vertical, linear, functional perspective toward a horizontal, process-centric one. Agent technologies may, in this context, constitute an element of the organizational information or knowledge system, where software agents support selected tasks within the framework of a specific business process. On the other hand, in the case of multi-agent systems, the process-centered approach comes to be applied in defining the system architecture. The use of software agents will make it easier to integrate distributed devices within business processes in which a human being participates, dynamically specify business processes with the participation of such devices and codify such processes as part of the concept of composite software, and consequently gain a competitive advantage by knowledge-based organizations thanks to the possibility of gaining new knowledge about processes and entities that take part in them. The use of semantic solutions in this process will aid the representation of knowledge gained in this way and its processing by IT technologies and by a human being. This way of codifying knowledge about dynamic business processes and entities that participate in them makes it possible to use agent societies also for the purpose of managing the knowledge that was obtained in this way. This paper is dedicated to a range of issues concerning the process-centric approach and software agent technologies to support organizations during the knowledge-based economy.
In the network-based DNC systems and especially heterogeneous DNC systems, data get more distributed due to the ability to store not only in the DNC Server, but also in the CNC controller or CNC Terminal. This presents a challenge to the DNC software in the implementation of its basic functions. The agent-based DNC software with assistants (ADNC) is suggested to solve the above problem. Its tasks are to collect distributed NC information, and transfer data safely as well as performing other extended functions, i.e. NC program generation, machine data collection, production data collection, control machines in system, etc. In this paper we presented our concept to develop the ADNC, and its first prototype. This prototype was developed in a process using a framework of agent-based assistants, called Agent AP. It is applicable on distributed manufacturing data and had been implemented on the agent platform JADE. The module Program Assistant, one of these prototype modules, which is responsible for management, bidirectional transfer, and monitoring change of NC programs, is also discussed.
