• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.795-802
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• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.544-553
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• 2005

In this paper, the research has been done to develop the inclination test items to form the desirable online learning community in which social interaction may be maximized, dropout rate lowered and learners' feeling of isolation eliminated. Once developed, the inclination test items have been classified into homogeneous ones and heterogeneous ones. And on the basis of the results of this research, Intelligent agent based Inclination Test Grouping e-learning System(IIGS) has been developed, which can perform automatic grouping of online leaning community by intelligent agent. The results of this research with 1,000 teachers in reality by means of developing the grouping system have shown that 151 groups are automatically formed. Among them, 34% have shown very high degree of learning satisfaction and intended to maintain the groups in the future.

• Korean Journal of Computational Design and Engineering
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• v.4 no.3
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• pp.210-223
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• 1999

An efficient management of product information is critical to the enhancement of corporate competitiveness. Product information is often distributed in term of organization, geography, and time. With the rapid increase in the use of Internet or its associated Web and intranets, it has been accelerating to integrate the distributed information. In this research, a Distributed, Open, Intelligent Product data Management system, namely DOI-PDM, is developed. This system deals with product information following the STEP standard, and its operation is controlled by a Web-based workflow management system. CORBA is employed to ensure interoperability among distributed objects. It is intended to achieve openness by using various standards, such s STEP, KQML, SGML, and WfMC specifications. One major difficulty in managing it needs also be properly modified according to the dynamics. It however is very hard to have a prior anticipation to the dynamics. It however is very hard to have a prior anticipation to the modification requirements in practice. We introduce a process adaptation model and a use of intelligent agent technology. An agent is delegated to modify process definitions during run-time. A method of agent implementation and a proper communication scheme among te agents are proposed. Also developed in this research is a STEP-based content search system which can co-work with the agents by providing relevant product information that the agents require.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2361-2368
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• 2009

Recently AI(Artificial Intelligence) is one of the issues in the on-line game, a research that a game character seems to be realistic and is progressing using AI technique. Especially NPC is an important part of the AI researches of on-line game, and it is concerned by a game player and an architect. We proposed an intelligent agent framework to implement the NPC technique after studying the NPC technique using context awareness that reacts to the PC(Player Character) actively. Also, it can be developed gradually, and apply to various application because it has the capability to of adding an agent or deleting an agent easily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.792-812
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• 2022

Multi-agent systems often need to achieve the goal of learning more effectively for a task through coordination. Although the introduction of deep learning has addressed the state space problems, multi-agent learning remains infeasible because of the joint action spaces. Large-scale joint action spaces can be sparse according to implicit or explicit coordination structure, which can ensure reasonable coordination action through the coordination structure. In general, the multi-agent system is dynamic, which makes the relations among agents and the coordination structure are dynamic. Therefore, the explicit coordination structure can better represent the coordinative relationship among agents and achieve better coordination between agents. Inspired by the maximization of social group utility, we dynamically construct a factor graph as an explicit coordination structure to express the coordinative relationship according to the utility among agents and estimate the joint action values based on the local utility transfer among factor graphs. We present the application of such techniques in the scenario of multiple intelligent vehicle systems, where state space and action space are a problem and have too many interactions among agents. The results on the multiple intelligent vehicle systems demonstrate the efficiency and effectiveness of our proposed methods.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.11-15
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• 2001

The explosion of the Internet, and most recently e-commerce, has caused great interest in agent technologies. The development of virtual environments has also increased in the last few years. A growing number of real-time applications use graphics with photorealistic quality, especially in the field of training, but also in the areas of design and ergonomic research. We describe an attempt to develop a framework that provides customers with multimedia information and interactive experiences with a virtual shopping environment. The application presented consists on a virtual visit to a music -store where the user is guided by an intelligent agent named Lizeth which responds in real-time to user's requests with precise information about music, artist's biographies, prices and related products to help the user to make decisions. The potential of UML and the Java programming language is discussed to show their application in the field of intelligent agents as mediators on shopping processes. We conclude that the proposed framework leads to the creation of application with a potentially significant impact in the development of e-commerce systems embedded in virtual environments.

• 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).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1938-1943
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• 2005

Network human-robot interface is an important research topic. In home application, users access the robotic system directly via voice, gestures or through the network. Users explore a system by using the services provided by this system and to some extend users are enable to participate in a service as partners. A service may be provided by a robot, a group of robots or robots and other network connected systems (distributed sensors, information systems, etc). All these services are done in the network environment, where uncertainty such as the unstable network connection, the availability of the partners in a service, exists. Moreover, these services are controlled by several users, accessing at different time by different methods. Our research aimed at solving this problem to provide a high available level, flexible coordination system. In this paper, a multi-agent framework is proposed. This framework is validated by using our new concept of slave agents, a responsive multi-agent environment, a virtual directory facilitator (VDF), and a task allocation system using contract net protocol. Our system uses a mixed model between distributed and centralized model. It uses a centralized agent management system (AMS) to control the overall system. However, the partners and users may be distributed agents connected to the center through agent communication or centralized at the AMS container using the slave agents to represent the physical agents. The system is able to determine the task allocation for a group of robot working as a team to provide a service. A number of experiments have been conducted successfully in our lab environment using Issac robot, a PDA for user agent and a wireless network system, operated under our multi agent framework control. The experiments show that this framework works well and provides some advantages to existing systems.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.609-616
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• 2001

Today, as the Internet is popularized, information and news retrieval are generalized. However due to the tremendous amount and variety of information, many users appeal the difficulties of information retrieval. Thus in this paper, we propose a news retrieval system, which filters news articles using an intelligent agent with the learning ability of BPN (back propagation neural network). This system also uses a profile to accomodate the personalized news retrieval. This system consists of two major agents, collection agent and learning agent. The collection agent gathers the articles from several news sites, analyzes them, and stores into a database. The learning agent builds the BPN based on the personalized data. In addition, considering the popularity of the wireless internet due to the rapid development of communication technologies, we made this system provide the service through the wireless internet.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.167-172
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• 2002

Recently, some of people are keep in research and development of the further more efficient and convenient auction systems using intelligent software agents in electronic commerce. The purpose of this thesis is that a simple auction system has web bulletin boards, is aided by intelligent agent, and generates pertinent auction duration time and starting price for auction goods of auctioneer into a auction system, then the auctioneer gets the highest margin. The seller who want to sell goods, is using internet sends mail that has information for goods to agent of internet auction system. The agent undertake filtering process for already learned information about similar goods. And it calculate duration time and start price from stored bidding history database. In this thesis we propose a mailing agent system pushing information in internet auction that enables to aid decision for auctioneer about the starting time and price which delivers the highest margin.