• Journal of Information Technology Applications and Management
• /
• 제16권1호
• /
• pp.1-20
• /
• 2009

Negotiation is a process of reaching an agreement on the terms of a transaction. such as price, quantity, for two or more parties. Negotiation tries to maximize the benefits for all parties concerned. instead of using human-based negotiation. the e-commerce environment provides such an environment as adopting automated negotiation. Thus. choosing agent technology is appropriate for an automatic electronic negotiation platform. since autonomous software agents strive for the best deal on behalf of the human participants. Negotiation agents need a clear-cut definition of negotiation models or strategies. In reality, most bargaining systems embody nearly one negotiation model. In this article. we present a mobile agent negotiation system with reusable negotiation strategies that allows agents to dynamically embody a user's favorite negotiation strategy which can be preinstalled as a component in the system. We develop a prototype system, which is fully implemented in compliance with FIPA specifications, and then. describe the benefits of using the system.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.154-154
• /
• 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

• 융합보안논문지
• /
• 제7권4호
• /
• pp.115-121
• /
• 2007

유/무선 망에서 통신 노드 간에 통신 실패로 이동 에이전트는 비록 망에서 일시적인 정보 서비스를 이용 할지 모르지만 모든 전송 정보가 블록되고 만다. 이러한 문제를 해결하기 위해 본 논문은 모바일 에이전트가 원할 한 전송을 보장받기 위한 경로 재순서 방법을 제안한다.

• Asia pacific journal of information systems
• /
• 제14권3호
• /
• pp.121-144
• /
• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.

• 한국정보처리학회논문지
• /
• 제6권7호
• /
• pp.1770-1776
• /
• 1999

최근 몇 년 동안 이동 에이전트(Mobile Agent) 기술은 분산 처리 시스템(Distributed Processing System)의 새로운 패러다임(Paradigm)으로 많은 관심이 되어왔다. 이동 에이전트는 통신망 노드에서 노드로 이주 가능한 자율적인 객체이다. 그러나, 통신망에 연동된 호스트(host)나 노드 결손 등으로 인해 이동 에이전트는 계속 처리할 수 있는 다른 노드들이 있을 지라도 무한 대기하거나 파괴될 수 있다. 이를 위해서, 본 논문은 이동 에이전트의 이주를 보장하기 위한 경로 재조정과 후위복구 기법을 통한 효율적인 이주 정책을 제안한다. 제안된 이주 정책은 가능한 한 자율적으로 이동 에이전트의 이주 신뢰를 제공하고, 자바(Java) 언어로 개발된 이동 시스템 모델인 MOS에서 이를 구현한다.

• 정보처리학회논문지D
• /
• 제13D권1호
• /
• pp.37-50
• /
• 2006

최근 무선인터넷의 중요성이 강조되면서 모바일 단말 장치는 모바일 비즈니스 프로세스에서 중요한 역할을 담당한다. 특히, 모바일 단말 장치는 차세대 기술인 임베디드와 유비쿼터스 컴퓨팅의 주요 단말 장치이며 개발 대상이기도 하다. 또한, 모든 환경이 무선 인터넷 환경으로 이동되면서 무선 컴퓨팅 환경으로 도입하기 위한 서비스 기술에 많은 관심을 갖게 되었다. 그 중에서도 모바일 에이전트는 기존 인터넷 하부 구조상에 기능들을 전개하는 새로운 추상화 개념을 제공하며, 이러한 시스템은 융통성, 적용성, 확장성, 자율성 등을 요구하고 있다. 그러므로 이를 위해서는 새로운 소프트웨어 개발 방법론의 적용을 통해 해결하는 것이 중요하다. 따라서, 본 논문에서는 플러그 가능하고 독립성이 보장되는 조립 가능한 컴포넌트를 기반으로 에이젼트 아키텍처 모델을 작성한다 이러한 접근은 서블릿으로 컴포넌트 랩핑을 전개할 수 있으며, 이는 PDA 모바일 에이젼트를 개발하기 위한 모델과 컴포넌트에 대한 연구로 행해진다.

• 한국정보기술학회 영문논문지
• /
• 제9권2호
• /
• pp.55-63
• /
• 2019

Vehicle communication networks have some deficient network resources to support a vast multimedia service including safety driving information, video, news and some broadcast relayed from the playgrounds such as professional baseball games for autonomous vehicles. This paper deals with the framework for providing seamless multimedia service including safety driving information using multicast in cooperated-connected vehicle communication network (CVCN). It adopts smart-switch (SS) and smart intelligent multicast agent(SIMA) to support the seamless multimedia service. The SS manages and switches multimedia streams through SIMA in CVCN network. The SIMA to operate as an access point, is composed of multicast supporting part and control part of mobile devices/autonomous vehicles in CVCN network. Therefore this proposed technique using SS and SIMA within CVCN network is a new framework for multimedia service that can disperse the load of server.

• International Journal of Control, Automation, and Systems
• /
• 제1권2호
• /
• pp.229-235
• /
• 2003

We designed a family of completely autonomous mobile robots with local intelligence. Each robot has a number of on-board sensors, including vision, and does not rely on global positioning systems The on-board embedded controller is sufficient to analyze several low-resolution color images per second. This enables our robots to perform several complex tasks such as navigation, map generation, or providing intelligent group behavior. Not being limited to playing the game of soccer and being completely autonomous, we are also looking at a number of other interesting scenarios. The robots can communicate with each other, e.g. for exchanging positions, information about objects or just the local states they are currently in (e.g. sharing their current objectives with other robots in the group). We are particularly interested in the differences between a behavior-based approach versus a traditional control algorithm at this still very low level of action.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.164.1-164
• /
• 2001

Q-learning is a recent reinforcement learning algorithm that does not need a modeling of environment and it is a suitable approach to learn behaviors for autonomous agents. But when it is applied to multi-agent learning with many I/O states, it is usually too complex and slow. To overcome this problem in the multi-agent learning system, we propose the successive Q-learning algorithm. Successive Q-learning algorithm divides state-action pairs, which agents can have, into several Q-functions, so it can reduce complexity and calculation amounts. This algorithm is suitable for multi-agent learning in a dynamically changing environment. The proposed successive Q-learning algorithm is applied to the prey-predator problem with the one-prey and two-predators, and its effectiveness is verified from the efficient avoidance ability of the prey agent.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.174-174
• /
• 2000

Q-learning, based on discrete state and action space, is a most widely used reinforcement Learning. However, this requires a lot of memory and much time for learning all actions of each state when it is applied to a real mobile robot navigation using continuous state and action space Region-based Q-learning is a reinforcement learning method that estimates action values of real state by using triangular-type action distribution model and relationship with its neighboring state which was defined and learned before. This paper proposes a new Region-based Q-learning which uses a reward assigned only when the agent reached the target, and get out of the Local optimal path with adjustment of random action rate. If this is applied to mobile robot navigation, less memory can be used and robot can move smoothly, and optimal solution can be learned fast. To show the validity of our method, computer simulations are illusrated.