• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.147-163
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• 2004

For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.370-388
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• 2015

The localization of multi-agents, such as people, animals, or robots, is a requirement to accomplish several tasks. Especially in the case of multi-robotic applications, localization is the process for determining the positions of robots and targets in an unknown environment. Many sensors like GPS, lasers, and cameras are utilized in the localization process. However, these sensors produce a large amount of computational resources to process complex algorithms, because the process requires environmental mapping. Currently, combination multi-robots or swarm robots and sensor networks, as mobile sensor nodes have been widely available in indoor and outdoor environments. They allow for a type of efficient global localization that demands a relatively low amount of computational resources and for the independence of specific environmental features. However, the inherent instability in the wireless signal does not allow for it to be directly used for very accurate position estimations and making difficulty associated with conducting the localization processes of swarm robotics system. Furthermore, these swarm systems are usually highly decentralized, which makes it hard to synthesize and access global maps, it can be decrease its flexibility. In this paper, a simple pyramid RAM-based Neural Network architecture is proposed to improve the localization process of mobile sensor nodes in indoor environments. Our approach uses the capabilities of learning and generalization to reduce the effect of incorrect information and increases the accuracy of the agent's position. The results show that by using simple pyramid RAM-base Neural Network approach, produces low computational resources, a fast response for processing every changing in environmental situation and mobile sensor nodes have the ability to finish several tasks especially in localization processes in real time.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.137-147
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• 2007

As Web-based online communities are rapidly growing, the agents in social groups need to know their measurable belief of trust for safe andsuccessful interactions. In this paper, we propose a computational model of trust resulting from available feedbacks in online communities. The notion of trust can be defined as an aggregation of consensus given a set of past interactions. The averagetrust of an agent further represents the center of gravity of the distribution of its trustworthiness and untrustworthiness. And then, we precisely describe the relationship between reputation, trust, and averagetrust through a concrete example of their computations. We apply our trust model to online internet settings in order to show how trust mechanisms are involved in a rational decision-making of the agents.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.139-161
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• 2006

In this paper, we introduce a new combinatorial auction mechanism - N-Bilateral Optimized Combinatorial Auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers optimized trading for multi-suppliers and multi-purchasers in the supply chain. We design the N-BOCA system from the perspectives of architecture, protocol, and trading strategy. Under the given N-BOCA architecture and protocol, auctioneers and bidders have diverse decision strategies f3r winner determination. This needs flexible modeling environments. Hence, we propose an optimization modeling agent for bid and auctioneer selection. The agent has the capability to automatic model formulation for Integer Programming modeling. Finally, we show the viability of N-BOCA through prototype and experiments. The results say both higher allocation efficiency and effectiveness compared with 1-to-N general combinatorial auction mechanisms.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.207-212
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• 2004

This paper presents a reinforcement learning framework for stock trading systems. Trading system parameters are optimized by Q-learning algorithm and neural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently integrate global trend prediction and local trading strategy for obtaining better trading performance. Agents Communicate With Others Sharing training episodes and learned policies, while keeping the overall scheme of conventional Q-learning. Experimental results on KOSPI 200 show that a trading system based on the proposed framework outperforms the market average and makes appreciable profits. Furthermore, in view of risk management, the system is superior to a system trained by supervised learning.

• Journal of Information Management
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• v.32 no.1
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• pp.50-70
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• 2001

As todays's networks are typically heterogeneous and very often comprised of multi-platform, multi-vendor network components, mobile agents have been proposed as a solution to the problem of the management of increasingly heterogeneous networks. Mobile agents are no longer statically resident on managed devices for network management: in contrast, they are migratory, replaceable at any time as necessary, and may be equipped with mini expert systems which can diagnose and fix networks' faults on behalf of the manager. Therefore, in this paper, the MIB browsing facilities for network management using the JAMAS and mobile agents are implemented. That is, the network manager accesses the MIB information through mobile agents with which communicate the SNMP agent of each of managed devices. The implementation performance is also evaluated.

• Convergence Security Journal
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• v.6 no.1
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• pp.13-23
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• 2006

It is more desirable to execute AV software on server systems rather than on clients for the minimization of damages due to malicious codes. AV software on server system, however, may aggravate the load of server system. In this paper, we propose a new AV software executed on server system without additional loads with a monitor and multi-agent model. The new AV software supports dynamic load balancing that reflects the features of AV engine, and thus it can be executed efficiently on server systems. The results of performance evaluation on the AV software attest to the strong points of the new AV software.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.641-652
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• 2001

Most of current internet auction systems are single auction server program that partly automates the function of the conventional auction house. So these systems do not provide sufficient independence, distribution and parallelism between the functions of the conventional auction house. In these suction systems, only some of suction management facilities are automated by the server program, but still users need to execute a repetitive task to monitor the dynamic progress of a certain auction, decide the proper bid price, and submit the bid. Another problem is that they support only the single auctions such as English suction and Dutch auction, but they do not support the double auctions that are superior to the single auction in terms of speed, efficiency, and the fair distribution of profit. In this paper, we present are design and implement of an agent-based continuous double auction system, called CoDABot, in order to overcome the limitations of current auction systems. CoDABot supports the continuous double auction, provides various bidding agents for users to select, and has been implemented with a multi-agent system to realize more independent, and parallel subsystems.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.7
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• pp.778-787
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• 1999

이제까지 대부분의 다중 에이전트 시스템에서는 에이전트 사회에 속한 모든 응용 에이전트를 작업 요청에 관계없이 처음부터 구동시킨다고 가정하였다. 이러한 에이전트 정적 구동 방법은 에이전트 관리를 단순하게 해주는 이점을 제공하지만 워크플로우 관리나 전자상거래와 같이 매우 많은 수의 에이전트로 구성되는 응용 분야에서는 시스템 과부하와 자원의 낭비 등 많은 문제점을 초래한다. 동적 에이전트 관리는 이에 대한 해결책으로 아주 많은 수의 에이전트를 포함하는 다중 에이전트 시스템에서 현재 수행중인 작업에 관련된 에이전트만을 선별하여 구동시키고, 작업이 끝난 에이전트는 종료시킴으로써 자원의 낭비를 막고 에이전트간의 상호작용 시에 요구되는 에이전트 통신의 복잡도 부담을 감소시키는 효과를 낸다. 본 논문에서는 자바로 에이전트 관리 시스템을 구현하고, 이 관리 시스템을 통해 각기 다른 언어로 개발된 응용 에이전트가 분산된 환경에서 상호 협력을 통해 작업을 수행할 수 있는 기법을 제안한다. 사용자나 다른 에이전트의 요청으로 에이전트를 동적으로 수행시키기 위해 다른 언어로의 확장을 가능하게 하는 Java Native Interface(JNI)를 사용한 기술 및 이러한 이질적인 에이전트간의 원활한 통신을 위해서 KQML 언어 인터페이스를 통한 통신 기능을 제안한다. 이질적 에이전트의 동적 관리를 가능하게 함으로써 다중 에이전트 시스템의 자원 이용 효율성과 확장성을 높이고 다양한 환경 변화에 대한 적응성과 개선된 협동능력을 제공한다.Abstract It has been assumed that all application agents in a multi-agent system are pre-invoked and remain active regardless of whether they are actually used. Although this kind of static agent invocation simplifies the management of agents, it causes several problems such as the system overload and a waste of resources, especially in the areas of the workflow management and the electronic commerce that consist of tens and even hundreds of application agents. A solution for these problems is the scheme of dynamic agent management that selectively invokes only agents that are actually requested and terminates them when they are no longer needed. This method prevents a waste of system resources and alleviates the complexity of agent communications.This paper proposes an agent management system implemented in Java that supports interactions between application agents that are developed using different languages. Dynamic agent invocation is accomplished by Java Native Interface(JNI) that links two heterogeneous methods, and by KQML language interface that facilitates the communications between heterogeneous agents. This scheme of dynamic agent management provides efficient resource usage, easy extensibility, dynamic adaptibility to changes in the environment, and improved cooperation.