• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.156-163
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• 2001

Business forecasting is vital to the success of business. There has been an increasing demand for building business forecasting software system to assist human being to do forecasting. However, the uncertain and complex nature makes is a challenging work to analyze, design and implement software solutions for business forecasting. Traditional forecasting systems in which their models are trained based on small collection of historical data could not meet such challenges at the information explosion over the Internet. This paper presents an agent oriented business forecasting approach for building intelligent business forecasting software systems with high reusability. Although agents have been applied successfully to many application domains. little work has been reported to use the emerging agent oriented technology of this paper is that it explores how agent can be used to help human to manage various business forecasting processes in the whole business forecasting life cycle.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.1-21
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• 2003

As electronic commerce(EC) has grown rapidly, agents that work on the behalf of humans on the Internet are being used actively. However, most of the EC agents have some problems. They fail to fully support buyers' decision making behaviors and sellers' information supply activities. Further, they are not suited for mobile computing environment. In this paper, we introduce a Multi-Mobile Agents System(MMAS) that has been developed according to a conceptual framework that corrects the aforementioned problems. Built by using Tokyo IBM ASDK(Aglets Software Development Kit) for the area of hotel reservation, the system consists of buyer- and seller-side agents that interact with each other; buyer-side agents help buyers to make purchasing decisions by collecting and analyzing information through applying a multi-criteria decision making method, while seller-side agents substitute fur sellers by managing databases and providing real-time information to the buyer-side agents. In this system, multiple agents perform their shared tasks at the same time in order to increase efficiency. Users do not have to keep the connection with the system because they are notified when tasks are done.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.3
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• pp.125-134
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• 2014

This paper proposes a multi-agent message transport architecture to support application areas which need fast message communications for close collaboration among agents. In the FIPA(Foundation of Intelligent Physical Agents) agent platform, all message transfer services among agents are in charge of a conceptual entity named ACC(Agent Communication Channel). In our multi-agent message transport architecture, the ACC is represented as a set of system agents named MTSA(Message Transfer Service Agent). The MTSA enables close collaboration among agents by supporting asynchronous communication, by using Reactor pattern to handle agent input messages efficiently, and by selecting optimal message transfer protocols according to the relative positional relationships of sender agents and receiver agents. The multi-agent framework SMAF(Small Multi-Agent Framework), which is implemented on the proposed multi-agent message transport architecture, shows better performance on message transfer among agents than JADE(Java Agent Development Environment) which is a well-known FIPA-compliant multi-agent framework. The faster the speed of message transfer of a multi-agent architecture becomes, the wider application areas the architecture can support.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.243-246
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• 2002

It is expected that intelligent broadcasting service (IBS) will be able to provide broadcast programs based on user preference and program-associated information (metadata) in order to assist users to easily navigate the program contents being broadcast. So users can access program contents anytime/anywhere in the way they want. In this paper we propose a framework for IBS based on an intelligent software agent platform so called FIPA (Foundation for Intelligent Physical Agents). We use an FIPA implementation. so called FIPA-OS, as a platform for exchanging user preferences and program information as FIPA messages between a server and clients. The user preference is modeled as the User Preference description scheme in MPEG-7 MDS (Multimedia Description Scheme).

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1062-1072
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• 2006

Recently, new intelligent service frameworks, such as ubiquitous computing are proposed. So, the necessity of adaptive agent system has been increased. In this paper, we propose an intelligent service agent to help that ubiquitous computing system offer user suitable service in ubiquitous computing environment. In order to offer user suitable uT-service, an intelligent service agent mediates the gap between the context information in uT-service system, and user preference is reflected in it. Therefore, we focus on following three components; the first is suitable multi agent framework-agent communication analysis and applicable method of inference engine, the second is uT-ontologies to describe various context information-context information sharing between agents and context information understanding between agents, the third is learning method of user profile to apply in uT-service system. This approach enables us to build adaptive uT-service system to offer suitable service according to user preference.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.489-497
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• 2001

This paper describe design and implementation of a medical multi-agent system platform called MAMI (Multi-Agent system for Medical Image), which provides intelligent medical information services. The most important component of MAMI is a medical multi-agent system platform that supports a physical environment that medical agents can be deployed. MAMI follows FIPA (Foundation for Intelligent Physical Agent)\`s agent management reference model. In MAMI, COM(Common Object Model) and XML (eXtensibel Markup Language) for encoding ACL (Agent Communication Language) are used for multi-agent communications. In MAMI, a medical staff is conceptualized as an agent and integrated with multi-agent systems. MAMI agent platform provides an infrastructure applicable to share necessary knowledge between human agents and software agents. So MAMI makes intelligent medical information services easier.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.579-586
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• 2003

Agents are well fitted to e-commerce applicable area because they pursuit an autonomy and interact with dynamic environment. In this paper we propose an e-commerce agents using reinforcement learning. We modify a reinforcement teaming algorithm for agents to have an intelligent feature and to make a transaction as practical business body in behalf of a person. To show the validity of this approach, we classify agents into buying agents and soiling agents, give characters of level according to the degree of learning and communication. Finally we implement an e-commerce framework and show the result. In this paper we show a design of e-commerce agents which is based on the proposed learning algorithm and present that the agents have enough possibility of doing a transaction in practical e-commerce.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.253-255
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• 2003

We address an integrated multimedia framework based on a software agent platform for context-aware multimedia computing. We adopt the FIPA (Foundation for Intelligent Physical Agents) platform which provides agent communications and management mechanisms. In order to express context information, we use MPEG-21 metadata for describing user characteristics and usage environment. We encapsulate such context information as a FIPA message to be delivered between agents. Based on context information, appropriate multimedia content delivery becomes possible. We present our system implementation with a use case scenario and show that our proposed framework is effective for context-aware multimedia computing so that personalization of multimedia consumption can be possible.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.207-216
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• 2000

Due to recent growing interest in autonomous software agents and their potential application in areas such as electronic commerce, the autonomous negotiation become more important. Evidence from both theoretical analysis and observations of human interactions suggests that if decision makers have prior information on opponents and furthermore learn the behaviors of other agents from interaction, the overall payoff would increase. We propose a new methodology for a strategy finding process using data mining in autonomous negotiation system ; ANSIA (Autonomous Negotiation System using Intelligent Agent). ANSIA is a strategy based negotiation system. The framework of ANSIA is composed of following component layers : 1) search agent layer, 2) data mining agent layer and 3) negotiation agent layer. In the data mining agent layer, that plays a key role as a system engine, extracts strategy from the historic negotiation is extracted by competitive learning in neural network. In negotiation agent layer, we propose the autonomous negotiation process model that enables to estimate the strategy of opponent and achieve interactive settlement of negotiation. ANISIA is motivated by providing a computational framework for negotiation and by defining a strategy finding model with an autonomous negotiation process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.572-575
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• 2004

Since the 1990s, the advancement of semiconductor technology has resulted in the development of microprocessor technology, auxiliary computer technology, and application technology such as intelligent algorithms (neural network, fuzzy, etc.). These based the development of intelligent machines. An agent is autonomous software that recognizes environment, exchanges knowledge with other agents and makes decisions. We designed agent-based sensor structure. For the purpose, first, it modeled the function of an intelligent machine. Second, it designed sensory function on the agent level.