• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.824-831
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• 2009

This paper proposes an obstacle avoidance algorithm for an autonomous mobile robot. The proposed method based on the circular navigation with probability distribution finds local-paths to avoid collisions. Futhermore, it makes mobile robots to achieve obstacle avoidance and optimal path planning due to the accurate decision of the final goal. Simulation results are included to show the feasibility of the proposed method.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.89-94
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• 2002

In this paper, a protection system using a Multi-Agent concept for power distribution networks is proposed. Every digital over current relay(OCR) is developed as an agent by adding its own intelligence, self-tuning and communication ability. The main advantage of the Multi-Agent concept is that a group of agents work together to achieve a global goal which is beyond the ability of each individual agent. In order to cope with frequent changes in the network operation condition and faults, an OCR agent, suggested in this paper, is able to detect a fault or a change in the network and find its optimal parameters for protection in an autonomous manner considering information of the whole network obtained by communication between other agents. Through this kind of coordination and information exchanges, not only a local but also a global protective scheme is completed. Simulations in a simple distribution network show the effectiveness of the suggested protection system.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• 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 Korean Society for Precision Engineering
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• v.29 no.4
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• pp.373-379
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• 2012

Disruptions in manufacturing systems caused by system changes and disturbances such as the tool wear, machine breakdown, malfunction of transporter, and so on, reduce the productivity and the increase of downtime and manufacturing cost. In order to cope with these challenges, a new method to build an intelligent manufacturing system with biological principles, namely an ant colony inspired manufacturing system, is presented. In the developed system, the manufacturing system is considered as a swarm of cognitive agents where work-pieces, machines and transporters are controlled by the corresponding cognitive agent. The system reacts to disturbances autonomously based on the algorithm of each autonomous entity or the cooperation with them. To develop the ant colony inspired manufacturing system, the disturbances happened in the machining shop of a transmission case were analyzed to classify them and to find out the corresponding management methods. The system architecture with the autonomous characteristics was generated with the cognitive agent and the ant colony technology. A test bed was implemented to prove the functionality of the developed system.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.955-972
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• 2003

As the next significant software abstraction, software agents have generated lots of excitements in recent years because of its promise as a new paradigm for conceptualizing, designing, and implementing software systems. This promise is particularly attractive for creating software that operates in environments that are distributed, open, and complex, such as the Internet. The effort of developing agent systems have, however, suffered from lack of generalized agent architecture because of various properties of an agent and nonexistence of a standard agent architecture. An agent architecture is an important criterion in order to not only identify agents in their domain but also determine the software architecture of the system. The major contribution of the work described here is an object-oriented design of an agent architecture that addresses fundamental properties, which are autonomy and interaction. Object-oriented design method is used for identifying the internal modules of an agent architecture and organizing correlation between the modules are identified.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.6
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• pp.227-235
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• 2006

In this paper, autonomous separation methodology of faulted section based on network is proposed newly, which can minimize the outage effect as compared with the existing center-based faulted section separation method by determining and separating autonomously the faulted section by the free operation information exchange among IEDs on the feeder of distribution system. The all IEDs is designed in network in which client/server function is possible in order to separate autonomously the faulted section using PtP(Peer to Peer) communication. Also, Inference based solution of IED for the autonomous faulted section separation is designed by rules obtained from the analyzing results of distribution system topology. Here, the switch IEDs transmit on network the fault information utilizing on multi-casting communication method, at the fame time, determine selfly whether they operates or not by inferencing autonomously the faulted section using the inference-based solution after receiving the transmitted information. Finally, in order to verify the effectiveness and application possibility of the proposed methodology, the diversity fault cases are simulated for the typical distribution system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.2
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• pp.34-43
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• 2022

In Efforts to prevent CFIT accidents so far, have been emphasizing various education measures to minimize the occurrence of human errors, as well as enforcement measures. However, current engineering measures remain in a system (TAWS) that gives warnings before colliding with ground or obstacles, and even actual automatic avoidance maneuvers are not implemented, which has limitations that cannot prevent accidents caused by human error. Currently, various attempts are being made to apply machine learning-based artificial intelligence agent technologies to the aviation safety field. In this paper, we propose a deep reinforcement learning-based artificial intelligence agent that can recognize CFIT situations and control aircraft to avoid them in the simulation environment. It also describes the composition of the learning environment, process, and results, and finally the experimental results using the learned agent. In the future, if the results of this study are expanded to learn the horizontal and vertical terrain radar detection information and camera image information of radar in addition to the terrain database, it is expected that it will become an agent capable of performing more robust CFIT autonomous avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.154-154
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• 2000

The cooperative strategy for the teleoperated multi-agent system is presented. And this scheme has been applied to the teleoperated robot soccer system that is newly proposed. For the teleoperated robot soccer system, we made mapping functions to control a 2-wheeled mobile robot using a 2 DoF stickcontroller. The simulation with a real stickcontroller has been evaluated the performance of the proposed mapping function. Then, the basic cooperation strategy has been tested between teleoperated robot and autonomous robot It is shown that the multi-agent system for teleoperation can have a good performance for a job Like a scoring a goal

• The Plant Pathology Journal
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• v.34 no.3
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• pp.171-181
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• 2018

Fruit rot is the principal phytopathological problem of pipiana pumpkin (Cucurbita argyrosperma Huber) in the state of Guerrero. The aims of this research were to 1) identify the causal agent of southern blight on pumpkin fruits by morphological, pathogenic, and molecular analysis (ITS1, 5.8S, ITS2); 2) evaluate in vitro Trichoderma spp. strains and chemical fungicides; and 3) evaluate under rainfed field conditions, the strains that obtained the best results in vitro, combined with fungicides during two crop cycles. Number of commercial and non-commercial fruits at harvest, and seed yield ($kg\;ha^{-1}$) were registered. Morphological, pathogenic and molecular characterization identified Sclerotium rolfsii as the causal agent of rot in pipiana pumpkin fruits. Now, in vitro conditions, the highest inhibition of S. rolfsii were obtained by Trichoderma virens strain G-41 (70.72%), T. asperellum strain CSAEGro-1 (69%), and the fungicides metalaxyl (100%), pyraclostrobin (100%), quintozene (100%), cyprodinil + fludioxonil (100%), and prochloraz (100%). Thiophanate-methyl only delayed growth (4.17%). In field conditions, during the spring-summer 2015 cycle, T. asperellum strain CSAEGro-1 + metalaxyl, and T. asperellum + cyprodinil + fludioxonil, favored the highest number of fruits and seed yield in the crop.