• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.49-61
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• 2008

Most battleship warfare M&S systems run relatively slow and the simulation results are often unfair since the system should interact with human operators(controller and/or gamer). To deal with these problems, we have proposed the agent-based battleship warfare M&S system which interact with multiple agent systems instead of human operators. Agent-based M&S system may be able to efficiently support the analysis of effectiveness and/or the operational tactics development of given warfare by providing autonomous reasoning capabilities without the intervention of human controller. To do this, the paper propose the design concept and methodology using the advanced modeling and simulation framework as well as autonomous agent design principle. Several simulation tests performed on the battleship warfare case study on Korea Yellow sea will illustrate our techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.102-107
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• 2021

This paper discusses the containment control problem for multi-agent systems with input saturations. The goal of the containment control is to obtain swarming behavior by driving follower agents into the convex hull which is spanned by multiple leader agents. This paper considers multiple leader agents moving at the same constant speed. Then, to solve the containment problem for moving leaders, we propose a PI-based distributed control algorithm. We next analyze the convergence of follower agents to the desired positions. Specifically, we apply the integral-type Lyapunov function to take into account the saturation nonlinearity. Then, based on Lasalle's Invariance Principle, we show that the asymptotic convergence of error states to zero for any positive constant gains. Finally, numerical examples with the static and moving leaders are provided to validate the theoretical results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.497-500
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• 2004

가상현실은 현실세계에서 경험하기 어려운 환경을 간접적으로 경험할 수 있는 가상의 공간이다. 이러한 가상현실에는 건물, 지형, PC(Playable Character), NPC(Non-Playable Character)등의 다양한 객체들이 존재하게 되며, PC와 NPC와 같은 객체들은 현실감을 주기 위해 인공지능을 가지게 된다. 현재까지 인공지능에 대한 많은 연구가 진행되었으며, 다양한 분야에서 활용되고 있다. 가상현실에서는 유한상태 기계(Finite Sate Machine, FSM), 유전자 알고리즘, 신경망 알고리즘 $A{\ast}$ 알고리즘 등이 활용되고 있으며, FSM은 비교적 알고리즘이 간단하고, 다른 알고리즘에 비해 구현이 간단해 널리 이용되고 있다. 본 논문에서는 FSM을 활용하여 여러 행동 패턴을 정의하고 행동 패턴간 천이가 이루어 짐으로, 객체의 행동을 다양하게 나타낼 수 있는 Multiple FSM은 제안한다.

• Journal of radiological science and technology
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• v.43 no.5
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• pp.383-388
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• 2020

High-energy proton accelerators continue to be increasingly used in medical, research and industrial settings. However, due to the high energy of protons, a large number of secondary radiation occurs. Among them, neutrons are accompanied by difficulties of shielding due to various energy distribution and permeability. So In this study, we propose a shielding method that can shield neutrons most efficiently by using multiple-shielding material used as a decelerating agent or absorbent as well as a single concrete shielding. The flux of secondary neutrons showed a greater decrease in the flux rate when heavy concrete was used than in the case of ordinary concrete, and the maximum flux reduction was observed at the front position when using multiple shields. Multiple shielding can increase shielding efficiency more than single shielding however, As the thickness of the multiple shielding materials increased, the decline in flux was saturated. The mixture material showed higher shielding results than the polyethylene when using boron carbonate.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.11-22
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• 2004

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem(CSP) in which variables and constraints are distributed among multiple automated agents. ACSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CAPs. In recent years, many new backtracking algorithms for solving distributed CSPs have been proposed. But most of all, they have common drawbacks that the algorithm assumes the priority of agents is static. In this thesis, we establish a basic algorithm for solving distributed CSPs called dynamic priority search algorithm that is more efficient than common backtracking algorithms in which the priority order is static. In this algorithm, agents act asynchronously and concurrently based on their local knowledge without any global control, and have a flexible organization, in which the hierarchical order is changed dynamically, while the completeness of the algorithm is guaranteed. And we showed that the dynamic priority search algorithm can solve various problems, such as the distributed 200-queens problem, the distributed graph-coloring problem that common backtracking algorithm fails to solve within a reasonable amount of time. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-making. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.103-117
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• 2006

This study develops an agent-based simulation model to evaluate tourist information systems under ubiquitous environment. In this study, individual tourist's activity chaining behavior is formulated as a utility maximization problem. The underlying assumption of the model is that tourists increase their activities within their time and budget constraints to maximize their utilities. The model seeks individual's optimal tour schedule by solving Prize-Collecting Multiple-Day Traveling Salesman Problem(PC MD TSP). The simulation-based evaluation framework allows investigating individual utility gains by their information type and the total expenditure at each tour attractions. The real-time tour activity scheduling system enables tourists to optimize their tour activities by minimizing their time loss and maximizing their opportunity to use high utility facilities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.20
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• pp.123-138
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• 1989

The primary objective of the agency research in the game theory lives in the maintenance of Pareto is optimal condition for the optimal incentive contract. The basic concepts which are related to this objective are reviewed in connection with the general assumptions to model it, the moral hazard and adverse selection which arised from the information asymmetry, and finally the problem of risk distribution. The demand for auditing and the role of auditor have been addressed by ASOBAC. Issues which an auditor is explicitly introduced in a principal-agent framework have been addressed in this paper. These issues must be confronted to appropriately with the auditor, and to achieve an adequate understanding of optimal confronting arrangement with the auditor. The first step in introducing an auditor into this analysis is to examine the game-theoretic foundation of such a expended agency model. The Mathematical program formulated may not yield solution that are resonable. This arises because the program may call for the auditor and manager to play dominated Nash equilibra in some subgame. The nontrivial natures of the subgame implies that randomized strategies by the auditor and manager nay be of crucial importance. The possibilities for overcoming the randomized strategy problem were suggested; change the rule of the game and or impose covexity condition. The former seems unjustifiable in on auditing context, and the latter promising but difficult to achieve. The discussion ended with an extension of the revelation principle to the owner manager-auditor game, assuming strategies. An examination of the restriction and improvement direction of the basic concept of agency theory was addressed in the later part of this paper. Many important aspects of auditor incentives are inherently multiple-agent, multiple-period, multiple-objectine, phenomena and require further analyses and researches.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.25-33
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• 2001

In 1998, A. Young and M. Yung introduced the concept of ARC that conjugates functionalities of a typical PKI with the ability to escrow privte keys of the system users. Also in 1999, P. Paillier and M. Yung proposed a new notion - called SE-PKI -which presents other additional advantages beyond ARC. But SE-PKI system uses only one escrow agent. The storage of users secret information at a single agent can make it significant point of attack and arouse controversy about invasion of privacy. This paper presents SE-PKI key recovery system that multiple escrow agents can participate in it. Also, in our system, escrow agents can\`t recover user\`s ciphertext.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.145-150
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• 2001

A Controlled Ecological Life Support System(CELSS) is essential for man to live a long time in a closed space such as a lunar base or a mars base. Such a system may be an extremely complex system that has a lot of facilities and circulates multiple substances,. Therefore, it is very difficult task to control the whole CELSS. Thus by regarding facilities constituting the CELSS as agents and regarding the status and action as information, the whole CELSS can be treated as multi-agent system(MAS). If a CELSS can be regarded as MAS the CELSS can have three advantages with the MAS. First the MAS need not have a central computer. Second the expendability of the CELSS increases. Third, its fault tolerance rises. However it is difficult to describe the cooperation protocol among agents for MAS. Therefore in this study we propose to apply reinforcement learning (RL), because RL enables and agent to acquire a control rule automatically. To prove that MAS and RL are effective methods. we have created the system in Java, which easily gives a distributed environment that is the characteristics feature of an agent. In this paper, we report the simulation results for material circulation control of the CELSS by the MAS and RL.