• 산업경영시스템학회지
• /
• 제29권2호
• /
• pp.20-30
• /
• 2006

Due to recent growing interest in autonomous software agents and their potential application in areas such as electronic commerce, the autonomous negotiation become more important. Evidence from both theoretical analysis and observations of human interactions suggests that if decision makers have prior information on opponents and furthermore learn the behaviors of other agents from interaction, the overall payoff would increase. We propose a new methodology for a strategy finding process using data mining in autonomous negotiation system; ANSIA(Autonomous Negotiation System using Intelligent Agent). ANSIA is a strategy based negotiation system. The framework of ANSIA consists of three component layers; 1) search agent layer, 2) data mining agent layer and 3) negotiation agent layer. ANSIA is motivated by providing a computational framework for negotiation and by defining a strategy finding model with an autonomous negotiation process.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
• /
• pp.207-216
• /
• 2000

Due to recent growing interest in autonomous software agents and their potential application in areas such as electronic commerce, the autonomous negotiation become more important. Evidence from both theoretical analysis and observations of human interactions suggests that if decision makers have prior information on opponents and furthermore learn the behaviors of other agents from interaction, the overall payoff would increase. We propose a new methodology for a strategy finding process using data mining in autonomous negotiation system ; ANSIA (Autonomous Negotiation System using Intelligent Agent). ANSIA is a strategy based negotiation system. The framework of ANSIA is composed of following component layers : 1) search agent layer, 2) data mining agent layer and 3) negotiation agent layer. In the data mining agent layer, that plays a key role as a system engine, extracts strategy from the historic negotiation is extracted by competitive learning in neural network. In negotiation agent layer, we propose the autonomous negotiation process model that enables to estimate the strategy of opponent and achieve interactive settlement of negotiation. ANISIA is motivated by providing a computational framework for negotiation and by defining a strategy finding model with an autonomous negotiation process.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2005년도 추계학술대회 논문집
• /
• pp.980-983
• /
• 2005

An agent Is an autonomous process that recognizes external environment, exchanges knowledge with external machines and performs an autonomous decision-making function in order to achieve common goals. The techniques fur tackling complexity in software need to be introduced. That is decomposition, abstraction and organization. Agent-oriented model ing has the merits of decomposition. In decomposition, each autonomous unit may have a control thread. Thread is single sequential flow in program. The use of thread in agent modeling has an important meaning in the performance of CPU and the relation of autonomous units.

• 한국멀티미디어학회논문지
• /
• 제13권12호
• /
• pp.1820-1831
• /
• 2010

When interacting with unknown environments, an autonomous 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. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• 문화기술의 융합
• /
• 제5권1호
• /
• pp.361-369
• /
• 2019

ADAS 기능의 상용화에 따라 자율주행 시스템 체험에 대한 필요성이 높아지면서, 인공지능 에이전트의 역할이 주목받고 있다. 이 연구는 자기효능감 자극과 에이전트 체화 효과를 검증하기 위한 자율주행 체험 실험이다. 시뮬레이터 실험을 통해 자기효능감 자극의 유무, 에이전트 체화의 유무에 따른 사회적 실재감, 인지된 위험, 그리고 인지된 용이성 요인의 효과를 측정하였다. 분석 결과, 자기효능감 자극은 사회적 실재감, 인지된 위험에 긍정적 영향을 주고, 에이전트 체화는 인지된 용이성에 부정적 영향을 주는 것으로 확인되었다. 연구결과에 기반하여 부분자율주행 시스템의 수용도를 높일 수 있는 에이전트 설계 가이드라인을 제안하였다.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2005년도 춘계학술대회 논문집
• /
• pp.1050-1053
• /
• 2005

There is no agreed definition of intelligence. The ability to adapt to the environments is a kind of intelligence. Expert functionally recognize environment using their five senses, and acquire and memorize knowledge necessary for operating machines. Knowledge that they cannot acquire directly is acquired in indirect ways. The purpose of intelligence machines is applying to machines experts' knowledge acquisition process and their skills in operating machine. An agent is an autonomous process that recognizes external environment, exchanges knowledge with external machines and performs an autonomous decision-making function in order to achieve common goals. This paper describes agent application for intelligence machine.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권4호
• /
• pp.439-446
• /
• 2004

사용자 적응형 웹 서핑 시스템 설계를 위해 전체 시스템을 사용자 데이타 수집, 데이타 처리를 통한 사용자 프로파일 구축 및 개선, 그리고 사용자 프로파일의 적용을 통한 적응 등 세 단계로 나누어 접근할 수 있다. 본 연구가 설계한 세 부문의 에이전트들은 이들 각 단계에서 작업하며 상호 유기적인 협동을 통해 적응형 웹 서핑을 지원한다. 이들은 각각 대화식 인터페이스 에이전트(Interactive Interface Agent), 사용자 프로파일 에이전트(User Profile Agent), 그리고 자동항해 에이전트(Autonomous Navigation Agent)이다. 대화식 인터페이스 에이전트는 사용자 인터페이스를 제공하며 이를 통해 데이타를 수집하고 기계적 항해 지원을 수행한다. 사용자 프로파일 에이전트는 수집된 사용자 데이타를 처리하여 사용자 브라우징의 실시간에 사용자 프로파일을 동적으로 구축하고 갱신한다. 자동항해 지원 에이전트는 사용자 프로파일에 기초하여 사용자 관심과 가까운 웹 문서를 자동으로 선별하여 추천하는 자동 항해 모드를 제공한다. 본 연구가 제시하는 접근과 설계 방식은 향후 확장과 보완을 통해 실용 가능한 수준의 사용자 적응형 웹 서핑 시스템 구축에 활용될 수 있다.

• 한국정보시스템학회:학술대회논문집
• /
• 한국정보시스템학회 2000년도 추계학술대회
• /
• pp.1.4-4
• /
• 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.

• Educational Technology International
• /
• 제6권1호
• /
• pp.65-79
• /
• 2005

In a widely distributed environment, many occasions arise when people need to filter informationwith email clients. The existing information agents such as Maxims and Message Assistant have capabilities of filtering email messages either by an autonomous agent or by user-defined rules. FlexMA, a variation of FAMES (Flexible Asynchronous Messaging System) is proposed as an information filtering agent. Agents in our system can be scaled up to adapt user's various demands by controlling messages delivered among heterogeneous email clients. Several functionalities are split into each agent in terms of component configuration with the addition of multiple agents'cooperation and negotiation. User-defined rules are collected and executed by these agents in a semi-autonomous manner. This paper demonstrates how this design is feasible in a flexible message system.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제32권11호
• /
• pp.1084-1098
• /
• 2005

본 논문에서는 동적 환경에 적합한 자율 이동 에이전트의 이주 기법을 제안한다. 제안하는 이주 기법은 네트워크 및 시스템의 상태 변화에 적절하게 대응할 수 있도록 에이전트의 이주 경로를 동적으로 생성한다. 에이전트의 이주 과정에서 전송해야 할 데이타량 및 에이전트의 인스턴스를 생성하기 위한 시간을 감소시키기 위해 다음에 이동할 목적지에 프리패칭 메시지를 전달하여 필요한 데이타를 미리 수신할 수 있도록 한다. 제안하는 이동 기법은 에이전트의 이주 과정에서 발생한 결함에 대처할 수 있도록 체크포인트 기법을 이용하여 에이전트의 상태를 유지하고 복구할 수 있도록 하는 기능을 제공한다. 제안하는 이주 기법의 우수성을 입증하기 위해 다양한 실험을 통해 기존 방법의 비교 분석을 수행한다.