• International Journal of Contents
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• 제12권1호
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• pp.25-43
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• 2016

An agent-centric event planning method is proposed for providing pedagogical experiences in an immersed environment. Two-level planning is required at in a macro-level (i.e., inter-event level) and an intra-event level to provide realistic experiences with the objective of learning declarative knowledge. The inter-event (horizontal) planning is based on search, while intra-event (vertical) planning is based on hierarchical decomposition. The horizontal search is dictated by several realistic types of association between events besides the conventional causality. The resulting schematic plan is further augmented by conditions associated with those agents cast into the roles of the events identified in the plan. Rather than following a main story plot, all the events potentially relevant to accomplishing an initial goal are derived in the final result of our planning. These derived events may progress concurrently or digress toward a new main goal replacing the current goal or event, and the plan could be merged or fragmented according to their respective lead agents' intentions and other conditions. The macro-level coherence across interconnected events is established via their common background world existing a priori. As the pivotal source of event concurrency and intricacy, agents are modeled to not only be autonomous but also independent, i.e., entities with their own beliefs and goals (and subsequent plans) in their respective parts of the world. Additional problems our method addresses for augmenting pedagogical experiences include casting of agents into roles based on their availability, subcontracting of subsidiary events, and failure of multi-agent event entailing fragmentation of a plan. The described planning method was demonstrated by monitoring implementation.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.179-185
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• 2001

Mobile agents have the unique ability to transport themselves from one system in a network to another. The ability to travel allows mobile agents to move to a system that contains services with which they want to interact and then to take advantage of being in the same host or network as the service. But most of conventional mobile agent systems require that the users or the programmer should give the mobile agent its detail behavioral script for accomplishing the given task. And during its runtime, such mobile agents just behave according to the fixed script given by its user. Therefore it is impossible that conventional mobile agents autonomously build their own plants and execute them in considering their ultimate goals and the dynamic world states. One way to overcome such limitations of conventional mobile agent systems is to develop an intelligent mobile agent system embedding a reactive planner. In this paper, we design both a model of agent mobility and a model of inter-agent communication based upon the representative reactive planning agent architecture called JAM. An then we develop an intelligent mobile agent system with reactive planning capability, IMAS, by implementing additional basic actions for agent moves and inter-agent communication within JAM according to the predefined models. Unlike conventional mobile agents. IMAS agents can be able to adapt their behaviors to the dynamic changes of their environments as well as build their own plans autonomously. Thus IMAS agents can show higher flexibility and robustness than the conventional ones.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.733-734
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• 2009

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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• pp.202-203
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• 2015

To promote the remodeling project it is important to get apartment residents' consent. It is significant variable to determine project to progress smoothly from planning stage which committee of association establishment sets up to establishment stage of association. On average, it takes about 1~1.6 year in planning phase which means before construction phase of remodeling. Therefore, it is very important issue to get apartment residents' consent in planning phase. In this research, we focused on residents' opinion and proposed solution of conflict with gathering residents' opinion to proceed remodeling project. By setting particular remodeling situation, related residents represented as agents made effort to efficient coordination to reduce total duration of decision making. Therefore, we proposed multi-agent based on fuzzy inference to simulate behavior of decision making on remodeling project effectively. From this method, optimal alternative is selected by considering each agents' attributes which represented by fuzzy set. This research will develope to further research for realizing concrete multi-agent based on fuzzy inference considering all stakeholders in remodeling project.

• 경영과학
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• 제21권3호
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• pp.39-54
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• 2004

This paper presents a multi-agent system for intelligent recommendation of travel plans to users. The goal of the system is to provide alternative and preferable travel plans to users when the availability of tickets is low such as in vacations, holidays, weekends, or peak seasons. The multiple agents in the system search for available alternatives for a target travel in collaboration with other agents and recommend best alternatives by analyzing them using a multi-criteria decision-making model. A prototype online travel support system was constructed and a simulation experiment was performed for evaluation and comparison with different travel planning strategies.

• 제어로봇시스템학회논문지
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• 제18권12호
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• pp.1073-1078
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• 2012

This paper deals with the trajectory planning of multi agent robots using complex potential theory for robot soccer. The complex potential theory is introduced, then the circle theorem is used to avoid obstacles, and the vortex pair is used to make precise kicking direction of robot. Various situations of robot soccer are simulated and the effect of vortex strength and the speed of robots are discussed and the better way to avoid obstacles and to kick the precise direction is found. The feasibilities of complex potential theory to apply for the multi agent robots are successful.

• 지능정보연구
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• 제13권3호
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• pp.47-61
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• 2007

기업 운영에서 SCM (Supply Chain Management)의 중요성이 인식되면서 공급, 생산, 분배 등의 기능들을 통합적으로 관리하는 새로운 접근법의 필요성이 커지고 있다. 이 접근법은 여러 다른 기능들의 의사결정 문제를 하나의 통합된 최적화 모델로 분석하는 방법이다. 특히 공급사슬의 통합적인 운영을 위해서는 이전의 확정적 방법론 보다는 보다 구매자와 공급자의 관계를 유연하게 통합해 줄 수 있는 방법론이 필요하다. SCM은 대규모 문제이고 또한 다양한 내외 요인에 의해 기존의 설정된 계획 내용이나 상황이 항시 동적으로 변경될 수 있기에, 이들 정보를 통합 계획에 반영될 수 있도록 하여야 한다. 본 연구에서는 SCM의 핵심이 되는 생산계획과 분배계획 문제들을 효율적으로 통합할 수 있는 유전 알고리즘 (Genetic Algorithm)을 제시하고, 유전 알고리즘을 기반으로 동적 SCM을 위한 멀티 에이전트 시스템을 구현한다. 한편 통합계획 문제에서 유전 알고리즘을 통해 100%에 근접하는 최적해를 구하였고, 통합계획으로 얻은 결과와 통합 계획을 하지 않은 경우의 결과 값에서 큰 차이를 확인 할 수 있었다.

• 한국멀티미디어학회논문지
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• 제12권12호
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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 Communications and Networks
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• 제8권1호
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• pp.123-131
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• 2006

Several distributed architectures, incorporating mobile agent technology, have been recently proposed to answer the scalability limitations of their centralized counterparts. However, these architectures fail to address scalability problems, when distributed tasks requiring the employment of itinerant agents is considered. This is because they lack mechanisms that guarantee optimization of agents' itineraries so as to minimize the total migration cost in terms of the round-trip latency and the incurred traffic. This is of particular importance when MAs itineraries span multiple subnets. The work presented herein aspires to address these issues. To that end, we have designed and implemented an algorithm that adapts methods usually applied for addressing network design problems in the specific area of mobile agent itinerary planning. The algorithm not only suggests the optimal number of mobile agents that minimize the overall cost but also constructs optimal itineraries for each of them. The algorithm implementation has been integrated into our mobile agent framework research prototype and tested in real network environments, demonstrating significant cost savings.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.579-582
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• 2009

최근에 증강현실 에이전트에 대한 관심의 증가로 인하여, 유비쿼터스 컴퓨팅 환경이나 사용자의 입력에 자율적으로 반응하거나 새로운 형태의 인터페이스로서 이에 대한 다양한 연구가 진행되고 있다. 하지만, 기존의 연구들은 에이전트의 반응생성을 위한 유비쿼터스 컴퓨팅 환경내의 컨텍스트와 실제 및 가상 공간에 존재하는 정보들의 활용 방안에 대한 연구가 부족하였다. 따라서 본 논문에서는 환경 정보와 사용자의 프로파일 정보, 그리고 사용자 중심의 컨텍스트의 활용해서 행동을 선택하고 계획하는 증강현실 에이전트의 행동생성 시스템을 제안하고자 한다. 에이전트의 내부는 Belief-Desire-Intention (BDI) 모델과 계층적 업무 네트워크 (HTN)내 검색을 통해서, 반응적 행동의 시퀀스를 선택한다. 행동의 시퀀스가 기본 행동들만으로 구성이 된 후, 에이전트는 이전 행동 및 입력의 종류에 따라서 행동의 적합성을 판단 및 적응을 수행한 후, 행동을 활성화 시킨다. 제안된 행동 생성 시스템은 행동을 통한 에이전트의 정보 전달이 요구되는 교육, 게임, 도우미 에이전트 등에서 응용이 가능할 것이다. 이렇게 계획된 행동을 통해서 증강현실 에이전트는 효과적인 정보 전달과 의사소통 능력을 사용자에게 보여줄 수 있을 것으로 기대된다.