• 한국CDE학회논문집
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• 제3권1호
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• pp.31-39
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• 1998

This paper deals with a development of the system that implements a collaborative design environment with some intelligent agents on the m. Intelligent agents can design collaboratively trough an interchange of messages in their special domains. Such a collaborative design of agents is achieved on the WWW. In this paper, we propose special agents named intercessor and DCM (Dynamic Connection Manager) and suggest new connection architecture using these agents in the WWW in order to improve the pre-existed agent connection architecture. The proposed agents are developed using Java language and JATLite API. We apply the these agents to the new architecture and show some possibilities that the agent connection architecture can be extended in the WWW Agents interchange messages with others using KOML (Knowledge Query and Manipulation Language), agent communication protocol and language, and deal with message autonomously according to their rule base. Agents register and connect dynamically trough the intercessor agent, and infer from their.

• 정보교육학회논문지
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• 제3권2호
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• pp.41-53
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• 2000

본 연구는 웹 기반 협력학습을 위한 시스템에서 학습자의 학습을 돕기 위한 멀티에이전트간의 통신에 관한 연구이다. 우선, 에이전트 시스템에 대한 전반적인 내용과 특정을 고찰하였고 에이전트 상호간의 통신인 KQML에 대하여 살펴보았다. 또한 협력학습을 위한 에이전트 기반의 시스템 구조와 에이전트간의 상호 통신 방법을 제시하였다. Java 언어를 이용하여 협력학습 시스템을 설계 구현하였으며 실험을 통하여 에이전트간의 통신에 의한 협력학습 시스템의 효율성을 고찰하였다.

• 전자공학회논문지CI
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• 제48권3호
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• pp.36-45
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• 2011

소셜러닝의 대표적 학습인 협력학습에서의 에이전트란 학습자에게 현황이든, 환경이든, 과제이든 설명해 줄 수 있거나, 보편적이고 일반적인 방법으로 독립적인 기능을 수행할 수 있는 것이다, 이를 위해서는 에이전트 사이에서의 의사소통에 관한 정보기술 표준화 방법이 요구된다. 본 연구는 협력학습에서 사용되는 각종 에이전트들의 의사소통에 관한 데이터 모델에 관한 기술을 제시한다. 따라서 이러닝 협력학습 환경을 지원하는 많은 에이전트들의 유형을 파악하고, 이 에이전트들 간의 상호 의사소통에 관한 규칙을 갖는 데이터 모델을 설계하여 그 요소들을 정의하고자 한다. 이렇게 제시된 표준화된 데이터 모델을 기반으로 하는 다중 에이전트 시스템은 여러 응용 에이전트가 독립된 프로세스로 활동할 수 있도록 정의된 통신 데이터모델에 의해 메시지 상호 교환이 가능해진다. 본 연구는 소셜러닝에서 주를 이루는 학습방법인 협력학습 중에서 다양한 에이전트를 활용하는 경우 이를 지원하는 에이전트간의 통신에 관한 의사소통 모델 응용을 통해 원활한 협력학습이 구현되도록 기여할 것으로 기대한다.

• ETRI Journal
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• 제43권6호
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• pp.1004-1012
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• 2021

The collaboration productively interacting between multi-agents has become an emerging issue in real-world applications. In reinforcement learning, multi-agent environments present challenges beyond tractable issues in single-agent settings. This collaborative environment has the following highly complex attributes: sparse rewards for task completion, limited communications between each other, and only partial observations. In particular, adjustments in an agent's action policy result in a nonstationary environment from the other agent's perspective, which causes high variance in the learned policies and prevents the direct use of reinforcement learning approaches. Unexpected social loafing caused by high dispersion makes it difficult for all agents to succeed in collaborative tasks. Therefore, we address a paradox caused by the social loafing to significantly reduce total returns after a certain timestep of multi-agent reinforcement learning. We further demonstrate that the collaborative paradox in multi-agent environments can be avoided by our proposed effective early stop method leveraging a metric for social loafing.

• Archives of Pharmacal Research
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• 제24권6호
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• pp.473-484
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• 2001

There is clearly a need for novel breast cancer chemopreventive agents with enhanced potency and specificity with tittle or no side effects. To this end, several new chemical moieties have been synthesized or isolated from natural sources. In this reviewal we have described some agents currently in use or under development for treatment or prevention of breast cancer, as well as our own strategies for the discovery of natural product modulators of estrogen biosynthesis and function. In particulars bioassay-guided fractionation of active plant extracts is a unique method for identifying agents with novel mechanisms of action, some of which should be useful for prevention of human cancer. Further, with the advent of combinatorial chemistry and high throughput screening, even greater progress may now be expected with natural product leads.

• 정보처리학회논문지D
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• 제9D권1호
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• pp.135-144
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• 2002

기존의 연구에 의하면 멀티미디어 시스템(Multimedia Systems)을 성공적으로 디자인하기 위해서는 다양한 관련분야의 전문가들 사이에 긴밀한 협력이 필요하다고 한다. 그러나, 그 전문가들은 서로 상이한 관점과 지식 체계를 가지고 있기 때문에 상호간 긴밀한 협력에 필수적인 지식을 공유하고 의견을 조율하는데 많은 어려움을 겪는다. 특히 최근 들어 멀티미디어 시스템 디자이너들이 가상의 팀(Virtual Team)을 형성하여 인터넷과 같은 컴퓨터 통신시스템을 활용함으로 해서 지식공유와 의견조율을 통한 협력은 한층 더 어렵게 되었다. 본 연구에서는 이러한 문제점을 해결하는 Designer's Cafe을 개발하는데 그 주요 목적을 두고 있다.

• 한국CDE학회지
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• 제8권1호
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• pp.58-65
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• 2002

Collaborative product commerce(CPC) involves many people working together with heterogeneous and distributed software applications. For such an environment, Workflow Management System(WFMS) can be useful for coordination of people, software agents and processes. It provides diverse services including automatic work muting, project management continuous process improvement and application integration. However, there are some limitations to apply WFMS to CPC environment due to inflexibility and lack of design support facilities. This paper identifies the problems and addresses possible approaches to overcome the difficulties.

• 전자통신동향분석
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• 제37권6호
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• pp.32-42
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• 2022

Recently, decentralized approaches to artificial intelligence (AI) development, such as federated learning are drawing attention as AI development's cost and time inefficiency increase due to explosive data growth and rapid environmental changes. Collaborative AI technology that dynamically organizes collaborative groups between different agents to share data, knowledge, and experience and uses distributed resources to derive enhanced knowledge and analysis models through collaborative learning to solve given problems is an alternative to centralized AI. This article investigates and analyzes recent technologies and applications applicable to the research of multi-agent collaboration of AI bots, which can provide collaborative AI functionality autonomously.

• 산업공학
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• 제19권1호
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• pp.53-61
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• 2006

We propose a new supply chain planning methodology for both a manufacturer and a distributor in order to find a global supply chain plan for functional product markets. Functional products as opposed to innovative products include the staples that people buy regularly from their nearby places to satisfy basic needs. In the functional product market, the distributor has an initiative of supply chain control and planning with a freedom to request any profit maximizing order quantities until the manufacturer refuses, whereas the manufacturer may not provide more than requested. In this paper, two independent agents on behalf of the manufacturer and the distributor are introduced, and supply chain planning can be conducted by collaboration between them. In addition, mathematical models and a numerical example are presented to show the possibility of the proposed methodology.

• Asia pacific journal of information systems
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• 제15권3호
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• pp.223-241
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• 2005

In spite of the rapid growth of mobile multimedia contents market, most of the customers experience inconvenience, lengthy search processes and frustration in searching for the specific multimedia contents they want. These difficulties are attributable to the current mobile Internet service method based on inefficient sequential search. To overcome these difficulties, this paper proposes a MOBIIe COntents Recommender System for Movie(MOBICORS-Movie), which is designed to reduce customers' search efforts in finding desired movies on the mobile Internet. MOBICORS-Movie consists of three agents: CF(Collaborative Filtering), CBIR(Content-Based Information Retrieval) and RF(Relevance Feedback). These agents collaborate each other to support a customer in finding a desired movie by generating personalized recommendations of movies. To verify the performance of MOBICORS-Movie, the simulation-based experiments were conducted. The results from this experiments show that MOBICORS-Movie significantly reduces the customer's search effort and can be a realistic solution for movie recommendation in the mobile Internet environment.