• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.591-597
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• 2001

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control school is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.413-420
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• 2005

In this paper, we apply software agents, which use fuzzy logic and make autonomous decisions according to state transitions, to car driving environment. We carry out an experiment on artificial intelligent car driving in terms of real-time reactive agents. Inference techniques for constructing real-time reactive agents consider the settings with max-product inference, n-fuzzy rules, and n-associatives ($A_l,\;B_l),\;{\ldots}(A_n,\;B_n$). Then we perform defuzzification processes, extract a central value, and work out inference processes.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.1-12
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• 2019

The role of Internet of Things (IoT) has been evolving from connectivity to intelligent and autonomous functions. The increase in the number of connected things and the volume of data has revealed the limit of cloud-based intelligent IoT. Meanwhile, the development of microprocessors for the IoT has enabled their intelligent decision making and reactions without the intervention of the cloud; this phase is referred to as the "autonomous IoT era." However, intelligence is not the only function of the IoT. When a cyber physical system (CPS) is running on the cloud, the real-time synchronization between the real and virtual worlds cannot be guaranteed. If a CPS is running on the IoT, both the worlds can be synchronized closely enough for a zero- time gap, i.e., achieving the goals of autonomous IoT. ETRI implements intelligence into the role of IoT and collaborates their decision making and reactions without the intervention of humans. Then, we focus on the development of a new IoT computing paradigm that enables human-like discussions.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.1.4-4
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• 2000

We present an autonomous distributed manufacturing system to plan the manufacturing process and the schedule based on a customer order, which considers the system efficiency as well as to the flexibly. In our system, an intermediate conceptual agent called process agent is introduced, of which the role is to create a plausible alternative for the working group to fulfill the given order. The process related decision such as process sequence, allocated facilities, schedule and cost is also made simultaneously. Given an order, several these process agents are created, and the optimum on is selected through a bidding mechanism. As a criterion of such a decision-making, we consider a concept of value which is determined by several factors such as cost, delivery, working ratio and so forth. Every agent consisting of the system makes decisions and actions so as to maximize its possessing value, and the overall behavior of the system is controlled by the value distribution.

• Journal of Korean society of Dental Hygiene
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• v.13 no.6
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• pp.925-932
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• 2013

Objectives : The purpose of the study is to improve autonomous decision-making ability by analyzing the relationship between autonomy and decision-making ability. Methods : The subjects were 176 dental hygienists in Busan. Self-reported questionnaire was fill out from May 2012 to January 2013. Results : The average of the degree of autonomy was $2.20{\pm}0.29$. Buddhists showed the highest score of $2.37{\pm}0.37$ (p<0.05). Buddhists had the higher education than other religions (p<.05). Clinical decision-making ability was $2.21{\pm}0.25$. Among the subcategories, statistically significant differences (p<.05) was shown by gender, degree of education, and religion in the domain of "Exploration of Choice and Alternatives"; Buddhists showed a higher score in the domains of "Assessment and Re-evaluation of Decisions" and "Review of Values and Goals," with significant difference of p<.05. Autonomy and clinical decision making revealed a positive correlation in the categories "Assessment and Re-evaluation of Decisions" (r=.518, p=.000), "Review of Values and Goals" (r=.610, p=.000), and "Investigation of Information and Synchronization of New Information" (r=.314, p=.000). Conclusions : To improve the performance of dental hygienists, working systems and training will be intensified to develop the autonomy and clinical decision making.

• Korean Management Science Review
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• v.18 no.2
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• pp.39-60
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• 2001

This Paper deals with a collaborative decision making procedure of web-based DSS for supply chain management (SCM). The seemingly autonomous DSS dedicated to each of mutually exclusive prob1em domains forms a communication network and cooperates each other for better SCM decision making. We a1so propose a hub-spoke information sharing model for the DSS network. In the hub-spoke model, an information hub at the center facilitates information exchange between DSS\\`s and controls the conversations defined by the series of XML messages between agents of DSS. A product ordering scenario where supply decision is triggered upon customer order is used to demonstrate the SCM decision procedure through a collaboration of the web-based DSS.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.312-318
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• 2022

Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

• ETRI Journal
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• v.37 no.5
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• pp.1032-1043
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• 2015

ETRI's Co-Pilot project is aimed at the development of an automated vehicle that cooperates with a driver and interacts with other vehicles on the road while obeying traffic rules without collisions. This paper presents a core block within the Co-Pilot system; the block is named "Co-Pilot agent" and consists of several main modules, such as road map generation, decision-making, and trajectory generation. The road map generation builds road map data to provide enhanced and detailed map data. The decision-making, designed to serve situation assessment and behavior planning, evaluates a collision risk of traffic situations and determines maneuvers to follow a global path as well as to avoid collisions. The trajectory generation generates a trajectory to achieve the given maneuver by the decision-making module. The system is implemented in an open-source robot operating system to provide a reusable, hardware-independent software platform; it is then tested on a closed road with other vehicles in several scenarios similar to real road environments to verify that it works properly for cooperative driving with a driver and automated driving.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.194-195
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• 2023

Recently, Maritime Autonomous Surface Ship(MASS) technology has attracted attention as a key technology for ship safety, efficiency, and economic feasibility in the marine field. Decision-making by the navigator's Situation Awareness (SA) for remote control on shore is expected to play an important role in ship collision avoidance. In this study, the navigator's decision-making time for the collision situation was measured.