• Journal of the Korean Professional Engineers Association
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• v.30 no.6
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• pp.59-67
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• 1997

As Information society evolves, there is a growing need that substitutes agents for users to do the given Jobs in distributed computing environments. Agents can retrieve and browse the diverse information via Internet, as the users request, and can deal with the complicated routine jobs on behalf of users with timeliness and efficiency. Especially, mobile agent can support the paradigm for distributed application programs in Internet environments. This is suitable to jump-to-jump model without any hesitations because agent moves. Agents can be applied to various applications, but we restrict it to market information retrieval in this paper. On recognizing a query about merchandise information by an user, agent by itself retrieves the corresponding information by navigating the Internet and informs the result to the user. In this paper, we review the mobile agent configuration to do this kind of work, propose the system architecture based on this review. By using this system, users can be free from complicated routine jobs and pursue his/her wishes to promote ones welfare.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.40-46
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• 2022

Recently, as the need for data access by integrating information in a distributed cloud environment increases in enterprise-wide enterprises, interoperability for collaboration between existing legacy systems is emphasized. In order to interconnect independent legacy systems, it is necessary to overcome platform heterogeneity and semantic heterogeneity. To solve this problem, middleware was built using EMRA (Extended MetaData Registry Access) based on ISO/IEC 11179. However, the designed middleware cannot guarantee the efficiency of information utilization because it does not have an adjustment function for each node's resource status and work status. Therefore, it is necessary to manage and adjust the legacy system. In this paper, we coordinate the correct data access between the information requesting agent and the information providing agent, and integrate it by designing a cooperative agent responsible for information monitoring and task distribution of each legacy system and resource management of local nodes. to make efficient use of the available information.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.151-155
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• 2001

Mobile agent technology has been the subject of much attention in the last few years, mainly due to the proliferation of distributed software technologies combined with the distributed AI research field. In this paper, we present a design of communication networks of agents that cooperate with each other for forwarding messages to the specific mobile agent in order to make the overall system location transparent. In order to make the material accessible to general intelligent system researchers, we present the general ideas abstractly in terms of the graph theory. In particular, a proxy network is defined as a directed acyclic graph satisfying some structural conditions. In turns out that the definition ensures some kind of reliability of the network, in the sense that as long as at most one proxy agent is abnormal, there agent exists a communication path, from every proxy agent to the target agent, without passing through the abnormal proxy. As the basis for the implementation of this scheme, an appropriate initial proxy network is specified and the dynamic nature of the network is represented by a set of graph transformation rules. It is shown that those rules are sound, in the sense that all graphs created from the initial proxy network by zero or more applications of the rules are guaranteed to be proxy networks. Finally, we will discuss some implementation issues.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.711-714
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• 2004

A project to develop internet based collaborative engineering environments using agent technology is started to develop an agent based soft system for design and performance analysis of centrifugal pumps. This paper introduces the feasible technology needed to construct a pump design system based on software agent.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.181-188
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• 2022

An intelligent distributed multi-agent system (IDMS) using reinforcement learning (RL) is a challenging and intricate problem in which single or multiple agent(s) aim to achieve their specific goals (sub-goal and final goal), where they move their states in a complex and cluttered environment. The environment provided by the IDMS provides a cumulative optimal reward for each action based on the policy of the learning process. Most actions involve interacting with a given IDMS environment; therefore, it can provide the following elements: a starting agent state, multiple obstacles, agent goals, and a cluttered index. The reward in the environment is also reflected by RL-based agents, in which agents can move randomly or intelligently to reach their respective goals, to improve the agent learning performance. We extend different cases of intelligent multi-agent systems from our previous works: (a) a proposed environment-clutter-based-index for agent sub-goal selection and analysis of its effect, and (b) a newly proposed RL reward scheme based on the environmental clutter-index to identify and analyze the prerequisites and conditions for improving the overall system.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.71-78
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• 2002

The mobile agent is receiving the attention as new technique to retrieve and to share the distributed contents on web-based educational systems. The retrieval using mobile agent uses the method that delivers the agent to accomplish a search in direct server in substitute for it is transmitted a many contents to accomplish an efficient search. This study proposed the model of retrieval system that shares and searches the distributed educational contents of the bulletin board and newsgroup by using the mobile agent. In order to evaluate the efficiencies of the system that is proposed, we did the comparison test on the search model of existing and proposing system. By a test result, we confirmed network traffics of proposed system are diminished. Moreover we gave proof the fact that the optimum search time of the mobile agent-based system is shortened.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.360-370
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• 1999

The paper proposed a basic architecture of an agent system to support exchange and sharing of design informations by means of ACL(Agent Communication Language) which can represent design informations and knowledges. Based on the architecture of the agent system a ship initial design agent system was implemented in order to show the effectiveness of the agent-based system. The basic architecture of the agent consists of an ACL handlerand CORBA(Common Object Request Broker Architecture) objects for the exchange of ACL messages in the heterogeneous and distributed environment. The ACL handler can process expressions of knowledge and manage communication messages among the agents. The paper mainly focuses on the implementation of the ACL handler. The ACL handler consist of a KQML(Knowledge Query and Manipulation Language) handler that manages KQML messages, a conversation module, and a content handler that handles message contents. The conversation modulo implements conversation policies and checks all messages if they are allowable and meaningful messages based on the conversation policies. The implemented agent-based system was applied to the ship initial design to show the handling procedure of the agent system.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.67-80
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• 2000

Distributed cooperative information system is the one that has various knowledge sources as well as problem solving capabilities to get information in a distributed and heterogeneous data environment. In a distributed cooperative information system. a control mechanism to facilitate the available information is very important. and usually the role of the control mechanism determines the behavior of the total system In this research. we proposed a model of the distributed cooperative information system which is based on the multi-agent paradigm. We also implemented a test system to show l its feasibility. The proposed system makes the knowledge sources into agents and a special agent called 'facilitator' controls the cooperation between the knowledge agents The facilitator uses the knowledge granularity level to determine the sequence of the activation of the agents. In other words. the knowledge source with simple but fast processing mechanism activates first while more sophisticated but slow knowledge sources are activated late. In an environment in which we have several knowledge sources for the same topic. the proposed system will simulate the focusing mechanism of human cognitive process.