• The Korean Journal of Applied Statistics
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• v.9 no.1
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• pp.203-214
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• 1996

In this tutorial note, we resolve debates generated by Exchange Paradox. In particular, we show that Bayesian solution is superior to frequentist's. Then, in terms of decision analysis, we show that any rational decision is superior to no-action policy.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.113-124
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• 2009

How can action learning program promote organizational learning performance and especially project based team performance in Web-based small and medium-sized enterprises (SMEs)? This article discusses the association between project based team in action learning program and the performance of Web-based SME to be learning organization. In the case of ALPACO, action learning program that promote employee communication behavior, knowledge sharing, and organizational learning are found to be positively associated with the project based team performance and organizational learning, The results indicate that action learning program in SMEs indeed associated with greater knowledge sharing, learning communication skills and changing organizational culture. Learning organization can be, in turn, positively developed by project based team through action learning program for creating competitive advantage, Also, this study offers further support for the practical perspective on learning organization performance. The evidence from this case study suggests that the project team in action learning program playa significant role in team performance and the development of learning organization of the firm. Therefore, in the future, Web-based SMEs should consider making investments in action learning program that encourage project team's effective management in decision making, knowledge sharing, and organizational learning.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2027-2032
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• 2003

For action selection as well as learning, simple associations between stimulus and response have been employed in most of literatures. But, for a successful task accomplishment, it is required that an animat can learn and express behavioral sequences. In this paper, we propose a novel action-selection-mechanism to deal with sequential behaviors. For this, we define behavioral motivation as a primitive node for action selection, and then hierarchically construct a network with behavioral motivations. The vertical path of the network represents behavioral sequences. Here, such a tree for our proposed ASM can be newly generated and/or updated, whenever a new sequential behaviors is learned. To show the validity of our proposed ASM, three 2-D grid world simulations will be illustrated.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.496-499
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• 2003

Support Vector Machines (SVMs) is applied to a practical problem as one of standard tools for machine learning. The application of Reinforcement Learning (RL) and SVMs in action of mobile robot is investigated. A technique to decide the action of autonomous mobile robot in practice is explained in the paper, The proposed method is to find n basis for good action of the system under unknown environment. In multi-dimensional sensor input, the most reasonable action can be automatically decided in each state by RL. Using SVMs, not only optimal decision policy but also generalized state in unknown environment is obtained.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.11-26
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• 1995

We have used various information technologies (IT) in group decision-making for increasing effectiveness and satisfaction of group decision-making process. Recently, a new form of IT so called Group Decision supprot System (GDSS) was introduced into group decision-making process. Previous experimental studies about effectiveness of GDSSS have been inconsistent and the results were mixed. There was no empirical studies about GDSS in Korea. In this study, we divide two groups-GDSS supported group and traditional face-to-face group and investigate impacts of GDSS on group decision-making processes and outcomes. An idea generation task for operational action plan development, implementing GEO's strategic vision, served as the decision-making context. Supported GDSS is GroupSystems V, which had been developed by Univ. of Arizona. It was translated by Korean. According to the results, Number of nonredundant ideas in GDSS group is two or three times more than Non-GDSS grop. GDSS group feel more equal status, have better interpersonal relationship, have more confidence on group decision than Non-GDSS group. But satisfaction of participants on decision-making process and outcome has not showed a significant difference between two groups. Because all of participants in GDSS group were novice to GDSS. With this results we suggest further studies on transforming western type GDSS to Korean decision-making culture. It will be cornerstone for development of GDSS in Korean desision-making culture. It will be cornerstone for devlopment of GDSS in Korean decsion making culture environment.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.256-261
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• 2017

The notion of System of Systems (SoS), which is composed by many independent systems (i.e., Constituent Systems, CS), has emerged in various domains including social infrastructure. It is widely expected that complex requirements, which cannot be achieved in each CS-level, will be achieved in an SoS-level. While verification of SoS-level goal achievement is one of the most important problems, concrete case studies on SoS modeling and verification are still rare. In this paper, we focus on the fact that each CS performs an action for its own purpose by its own decision-making mechanism. We propose a novel Action-Benefit-Cost (ABC) SoS model which caters to the independent decision-making mechanisms of CSs. Using an abstract SoS example, this proposal provides a case study for the modeling and quantitative verification of the ABC SoS model.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.358-367
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• 2003

We consider discrete-time factorial Markov Decision Processes (MDPs) in multiple decision-makers environment for infinite horizon average reward criterion with a general joint reward structure but a factorial joint state transition structure. We introduce the "localization" concept that a global MDP is localized for each agent such that each agent needs to consider a local MDP defined only with its own state and action spaces. Based on that, we present a gradient-ascent like iterative distributed algorithm that converges to a local optimal solution of the global MDP. The solution is an autonomous joint policy in that each agent's decision is based on only its local state.cal state.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.159-165
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• 2008

The ROK army has equipped ATCIS (Army Tactical Control Information System) for the Corps echelon to visualize the battlefield and reduce the reaction time. Due to the information&surveillance equipment, uncertainty and variance of the battlefield have been decreased. However decision making for the ground operations has not changed as it depends on knowledge of the commander and staffs. The War game process to select and assess the best CoA (Course of Action) also depends on the pros and cons due to the limitation of time and capability. For the balanced development between intangible and tangible military strength, a new decision making process which is quantitative and useful for the military is needed. In this study, we suggest a Fuzzy-AHP based decision making model to improve troop leading procedure which is useful to evaluate and reflect intangible characteristics of the battlefield.

• Journal of the Korea Computer Industry Society
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• v.9 no.1
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• pp.1-10
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• 2008

This treatise wishes to proposal of most suitable about happened patient's disease when a doctor achieves medical treatment action about patient and decision-making methodology that decide treatment does presentation low class informer. That is, when a doctor treats patient, case that do medical examination and treatment to experience about disease at medical examination and treatment process is general. In case is like this, unexpected treatment side effect can be happened doing not consider patient's special quality or conditions. Use a medical decision-making tool to minimize these problem. Treatise that see therefore investigated validity about if arrange medical decision-making system concept, and analyze several tools(decision-making tools) that help in decision-making, and can help in medical examination and treatment decision-making of most suitable.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.522-531
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• 2001

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.