• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.219-223
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used conditional probability and trapezoidal fuzzy number. Our goal of study is make an intelligent automatic navigation agent model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.1-6
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• 2004

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy conditional probability and trapezoidal. we proposed the model that can Process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition. Our goal of study is make an intelligent automatic navigation agent model.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.439-446
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• 2004

To design a user-adaptive web surfing system, we nay take the approach to divide the whole process into three phases; collecting user data, processing the data to construct and improve the user profile, and adapting to the user by applying the user profile. We have designed three software agents. Each privately works in each phase and they collaboratively support adaptive web surfing. They are IIA(Interactive Interface Agent), UPA(User Profile Agent), and ANA(Autonomous Navigation Agent). IIA provides the user interface, which collects data and performs mechanical navigation support. UPA processes the collected user data to build and update the user profile while user is web-surfing. ANA provides an autonomous navigation mode in which it automatically recommends web pages that are selected based on the user profile. The proposed approach and design method, through extensions and refinements, may be used to build a practical adaptive web surfing system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.824-831
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• 2009

This paper proposes an obstacle avoidance algorithm for an autonomous mobile robot. The proposed method based on the circular navigation with probability distribution finds local-paths to avoid collisions. Futhermore, it makes mobile robots to achieve obstacle avoidance and optimal path planning due to the accurate decision of the final goal. Simulation results are included to show the feasibility of the proposed method.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.74-78
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• 2009

This paper explains the design and implementation of the FDA(Fault Detection Agent) based on IP-USN. FDA is a system that is suitable for detecting software error for multimedia distance education running on home network environment based on IP-USN. This system consists of an ED, and ES. ED is an agent that detects an error by hooking techniques for multimedia distance education based on IP-USN environment. ES is an agent that is an error sharing system for multimedia distance education based on IP-USN environment.

• Speech Sciences
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• v.11 no.2
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• pp.181-192
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• 2004

This paper presents an efficient speech interactive agent rendering smooth car navigation and Telematics services, by employing embedded automatic speech recognition (ASR), distributed speech recognition (DSR) and text-to-speech (ITS) modules, all while enabling safe driving. A speech interactive agent is essentially a conversational tool providing command and control functions to drivers such' as enabling navigation task, audio/video manipulation, and E-commerce services through natural voice/response interactions between user and interface. While the benefits of automatic speech recognition and speech synthesizer have become well known, involved hardware resources are often limited and internal communication protocols are complex to achieve real time responses. As a result, performance degradation always exists in the embedded H/W system. To implement the speech interactive agent to accommodate the demands of user commands in real time, we propose to optimize the hardware dependent architectural codes for speed-up. In particular, we propose to provide a composite solution through memory reconfiguration and efficient arithmetic operation conversion, as well as invoking an effective out-of-vocabulary rejection algorithm, all made suitable for system operation under limited resources.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.515-519
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• 1998

최근 인터넷 서비스의 폭발적인 증가로 기존에 사용하고 있던 통신망은 용량과 속도 등에서 한계에 부딪치며 개별 사용자가 이용하는 서비스 품질이 점점 나빠지고 있다 실시간 인터넷 서비스의 등장은 이러한 상황을 더욱 악화시켜 새로운 고속의 통신망 하부구조를 도입하여 이를 해결하려는 요구가 증가하고 있다. 본 논문에서는 이와 같은 문제점을 해결하기 위한 인터넷 연동기술에 대한 발전 추이와 ATM망 기반의 초고속 정보통신망 환경에서 ATM 망과 인터넷간의 실시간 인터넷 서비스를 제공하기 위한 연동장치인 Eagis의 구조와 기능을 소개한다. 또한 실시간 멀티미디어 서비스를 제공하기 위한 Eagis의 서비스 브로커 기능 중에서 통합 Navigation Agent에 대한 기능과 설계를 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.246-251
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce system management. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using fuzzy theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.9-11
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• 2022

Applying Reinforcement Learning in everyday applications and varied environments has proved the potential of the of the field and revealed pitfalls along the way. In robotics, a learning agent takes over gradually the control of a robot by abstracting the navigation model of the robot with its inputs and outputs, thus reducing the human intervention. The challenge for the agent is how to implement a feedback function that facilitates the learning process of an MDP problem in an environment while reducing the time of convergence for the method. In this paper we will implement a reward shaping system avoiding sparse rewards which gives fewer data for the learning agent in a ROS environment. Reward shaping prioritizes behaviours that brings the robot closer to the goal by giving intermediate rewards and helps the algorithm converge quickly. We will use a pseudocode implementation as an illustration of the method.