• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.56-59
• /
• 1998

The rapid diffusion of the Internet and the World Wide Web is facilitating greater interaction - and potential opportunities for customization - between vendors and customers. For instance, virtual reality and multimedia technologies allow consumers to envision their designed products. The increasing pace of the business environment highlights the need to deploy intelligent systems in all stages of product design and production planning. This paper deals with a system to generate an appropriate product design by adapting customer preferences and constraints using the case based reasoning methodology. Moreover, intelligent agents are integrated with virtual reality technology to provide a friendly user interface.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.1
• /
• pp.86-93
• /
• 2012

This paper presents a new approach to solve the pursuit problem based on a univector field method. In our proposed method, a set of eight agents works together instantaneously to find suitable moving directions and follow the univector field to pursue and capture a prey agent by surrounding it from eight directions in an infinite grid-world. In addition, a set of strategies is proposed to make the pursuit problem more realistic in the real world environment. This is a general approach, and it can be extended for an environment that contains static or moving obstacles. Experimental results show that our proposed algorithm is effective for the pursuit problem.

• Nuclear Engineering and Technology
• /
• v.37 no.2
• /
• pp.127-138
• /
• 2005

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.699-702
• /
• 2000

The Internet has become widely used in many countries. In particular, a new emerging technology, the WWW (World Wide Web), which has become a major application of the Internet, has been rapidly developed. As a result, there are hundreds of millions of URLs (Uniform Resource Locators) on the WWW, and the total number of URLs is still explosively increasing. To get information from the WWW, we generally use Internet search engines. However, we cannot always get the actual information we want. Accordingly, we have solved this problem by constructing a prototype system based on agents by programming language Java for constructing a more effective search engine. This so-called “intelligent agent system on WWW” deletes redundant HTML (Hyper Text Markup Language) files and exchanges information about the existence of URLs. And we found that our prototype system is more powerful and effective than conventional search engines.

• Proceedings of the IEEK Conference
• /
• summer
• /
• pp.421-426
• /
• 2004

Analyzing adaptive possibilities of agents in multi-agents system, we have discovered new aspects of ambient intelligence in distributed modular systems using intelligent building blocks (I-BLOCKS) [1]. This paper describes early scientific researches related to technical design, applicable experiments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop ambient intelligence applications. The processing technology presented in this paper is embedded inside each DUPLO1 brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Blocks in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can do 'programming by building' and thereby create specific functionalities of a modular structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modem artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing applications in ambient intelligence (AmI) environments. To illustrate these possibilities, the paper presents a range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular systems. The paper also reports briefly about earlier experiments of I-BLOCKS in different research fields, allowing users to construct AmI applications by a just defined concept of modular artefacts [3].

• Journal of information and communication convergence engineering
• /
• v.20 no.3
• /
• pp.181-188
• /
• 2022

An intelligent distributed multi-agent system (IDMS) using reinforcement learning (RL) is a challenging and intricate problem in which single or multiple agent(s) aim to achieve their specific goals (sub-goal and final goal), where they move their states in a complex and cluttered environment. The environment provided by the IDMS provides a cumulative optimal reward for each action based on the policy of the learning process. Most actions involve interacting with a given IDMS environment; therefore, it can provide the following elements: a starting agent state, multiple obstacles, agent goals, and a cluttered index. The reward in the environment is also reflected by RL-based agents, in which agents can move randomly or intelligently to reach their respective goals, to improve the agent learning performance. We extend different cases of intelligent multi-agent systems from our previous works: (a) a proposed environment-clutter-based-index for agent sub-goal selection and analysis of its effect, and (b) a newly proposed RL reward scheme based on the environmental clutter-index to identify and analyze the prerequisites and conditions for improving the overall system.

• The Journal of Korea Robotics Society
• /
• v.2 no.4
• /
• pp.310-316
• /
• 2007

The paper proposes a human-following behavior of mobile robot and an intelligent space (ISpace) is used in order to achieve these goals. An ISpace is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to track a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to track the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and trackinging of the walking human with the mobile robot are presented.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.7
• /
• pp.584-590
• /
• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Journal of Digital Convergence
• /
• v.7 no.1
• /
• pp.175-183
• /
• 2009

With the development of enabling technologies such as wireless networking and various types of hand held-mobile devices, Mobile intelligent agent has been widely applied to various fields. Different views on capabilities, advantages, and disadvantages of mobile intelligent agent providing an ubiquitous access are brought by field researchers and practitioners recently. The purpose of this paper is thus to provide the discussion of the comtemporary development of mobile intelligent agent in the contexts of the Infosphere, focusing especially on developing and nurturing the future research grounds such as information scalability, and information security. The results of this study would improve the applications of mobile intelligent agents in web transaction, especially mobile business surroundings where many interest groups have to adjust their point of issues rapidly due to the changing business environment, i.e., customer's change the order item in web.

• Journal of the Korean Society for Railway
• /
• v.10 no.3 s.40
• /
• pp.350-354
• /
• 2007

Intelligent agent is to decide what customers need on the internet and offer them accurate information. In this paper, the system which can recommend the tourism items in terms of customer‘s needs is proposed by appling the intelligent agent to railway tourism system. Most of previous agents are focused on price. But, this study proposes the Railway tourism system which offers each customer the best suitable information based on quality of information and reputation. The customer's needs are analyzed through intelligent agent and the information which is suitable for customer's needs is obtained the Artificial Neural Network Model.