• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.543-545
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• 1998

Robotic soccer is multi-agent system playing soccer game under given rule. This system consists of three mobile robots, vision sensor, action decision module, action execution module and communication module. This paper presents new action decision method using multi-layer neural networks.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2010년도 추계학술대회
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• pp.199-207
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• 2010

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. In this paper, we use the analytic hierarchy process in weights calculating. For the purpose of making optimal decision, the data of three different smart phones models are used.

• 대한안전경영과학회지
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• 제6권2호
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• pp.177-186
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• 2004

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• 대한산업공학회지
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• 제32권2호
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• pp.141-152
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• 2006

This paper presents the development of a decision model to examine the optimal repair action for a deteriorating system. In order to make a reasonable decision, it is necessary to perform an analysis of the uncertainties embedded in deterioration and to evaluate the repair actions based on the expected future cost. Focusing on the power law failure model, the uncertainties related to deterioration are analyzed based on the Bayesian approach. In addition, we develop a decision model for the optimal repair action by applying a repair cost function. A case study is given to illustrate a decision-making process by analyzing the loss incurred due to deterioration.

• 한국멀티미디어학회논문지
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• 제23권7호
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• pp.830-839
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• 2020

As a popular mathematical framework for modeling decision making, Markov decision process (MDP) has been widely used to solve problem in many engineering fields. MDP consists of a set of discrete states, a finite set of actions, and rewards received after reaching a new state by taking action from the previous state. The objective of MDP is to find an optimal policy, that is, to find the best action to be taken in each state to maximize the expected discounted reward of policy (EDR). In practice, MDP is typically unknown, so simulation-based policy improvement (SBPI), which improves a given base policy sequentially by selecting the best action in each state depending on rewards observed via simulation, can be a practical way to find the optimal policy. However, the efficiency of SBPI is still a concern since many simulation samples are required to precisely estimate EDR for each action in each state. In this paper, we propose a method to select the best action accurately in each state using a small number of simulation samples, thereby improving the efficiency of SBPI. The proposed method accumulates the simulation samples observed in the previous states, so it is possible to precisely estimate EDR even with a small number of samples in the current state. The results of comparative experiments on the existing method demonstrate that the proposed method can improve the efficiency of SBPI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• 한국게임학회 논문지
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• 제11권6호
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• pp.61-70
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• 2011

본 논문에서는 결정트리 학습 알고리즘을 활용한 축구 게임 수비 NPC 제어 방법을 제안한다. 제안하는 방법은 실제 게임 사용자들의 이동 방향 패턴과 행동 패턴을 추출하여 결정트리학습 알고리즘에 적용한다. 그리고 학습된 결정트리를 바탕으로 NPC의 이동방향과 행동을 결정한다. 실험결과 제안하는 방법은 결정트리 학습에 시간이 다소 걸리지만, 학습된 결정트리를 바탕으로 이동방향이나 행동을 결정하는 시간은 약 0.001-0.003 ms(밀리초)가 소요되어 실시간으로 NPC를 제어할 수 있었다. 또한, 제안하는 방법은 현재 상태 정보 뿐만 아니라 이를 분석한 관계정보, 이전 상태 정보도 함께 활용하므로, 기존방법인 (Letia98)에 비해 이동방향 결정시 높은 정확도를 나타냈다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.960-968
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• 2005

The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

• 한국실내디자인학회논문집
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• 제22권6호
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• pp.98-107
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• 2013

Space evolves from the concept of deterministic static location to a dynamic, connected area through the interference of the user. While this does incorporate physical changes of the space, it also reflects the changes of the program or characteristics of the space through the actions and changes of the user. Therefore, in this study we plan to review the characteristic of time appearing within space, thereby discussing the impact of changing of condition in time-space to the decision making of the user. Further, we plan to analyze the specific causes, and subsequently introduce a new perspective over space. In order to achieve this, we need to first understand the reason why the attribute of time needs to be discussed in space, and perform a fundamental analysis of factors for the changes of the users' actions following changes in space-time condition. This means that space is not limited to merely satisfying its innate objective as an area, but may have a basis for modifying its role to help the decision making of the users caused by changes in space-time conditions. Accordingly, we analyze the factors for change of environment that can appear in space following the flow of time caused by correlation in space-time, as well as psychological factors and variables for decision making by the users. Based on this, we analyze cases to study the influence of condition changes in time-space on the action decision judgment of the users. Through this, we propose that the actions of the users can be determined following changes in time-space conditions, and discuss the need for changes in our perspective of space.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
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• pp.207-210
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• 2001

This Paper presents a design of the fuzzy decision maker analyzable of output result of ECG signals. The fuzzy decision maker proposed are divided into two groups whose functions are different each other. The one rules when decision of heart rates, The other decision values for an interval of each points of waveform using of which static state values and abnormal values. We have chosen several variable used for composing condition and action part by knowledge of an Expert The result of outputs with fuzzy rules suggested was a proved of satisfied with by classify ECG arrythmia signals