• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.6
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• pp.579-587
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• 2008

In collaborative environment, since each agent generally uses different words for the same meaning, there is an obstacle for information sharing. In collaborative product development environment, each agent has different words for representing same product information. As a result, it is hard to share product information in this situation. For solving this problem, semantic-based product information is needed. In this paper, a ontology-based semantic searching system which is able to interact with legacy PDM systems is proposed for product information sharing in collaborative environment Product ontology is represented with OWL format, and the product ontology is processed by Pellet reasoning engine for semantic searching. The system is implemented as a web service which can be integrated with other systems. This paper also introduces the approach with which a PDM system provides a function of semantic search with this search system.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.77-88
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• 2015

In this paper, we consider a two-agent single-machine scheduling problem with exponential job-dependent position-based learning effects. The objective is to minimize the total weighted completion time of one agent with the restriction that the makespan of the other agent cannot exceed an upper bound. First, we propose a branch-and-bound algorithm by developing some dominance /feasibility properties and a lower bound to find an optimal solution. Second, we design an efficient simulated annealing (SA) algorithm to search a near optimal solution by considering six different SAs to generate initial solutions. We show the performance superiority of the suggested SA using a numerical experiment. Specifically, we verify that there is no significant difference in the performance of %errors between different considered SAs using the paired t-test. Furthermore, we testify that random generation method is better than the others for agent A, whereas the initial solution method for agent B did not affect the performance of %errors.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• Korean Journal of Cognitive Science
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• v.14 no.3
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• pp.13-21
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• 2003

This study presents a design of Teachable Agent(TA) and its theoretical background. TA is an intelligent agent to which students as tutors teach, pose questions, and provide feedbacks using a concept map. TA consists of four independent Modules, Teach Module, Q&A Module, Test Module, and Resource Module. In Teach Module, students teach TA by constructing concept map. In Q&A Module, both students and TA ask questions and answer questions each other through an interactive window. To assess TA's knowledge and provide feedback to students, Test Module consists of a set of predetermined questions which TA should pass. From Resource Module, students can search and look up important information to teach, ask questions, and provide feedbacks whenever they want. It is expected that TA should provide student tutors with an active role in learning and positive attitude toward the subject matter by enhancing their cognition as well as motivation.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.427-432
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• 2012

The article herein suggested a compound repository and a descriptive method to develop a compound knowledge process. A data target saved in a compound knowledge repository suggested in this article includes all compound knowledge meta data and digital resources, which can be divided into the three following factors according to the purpose: user roles, functional elements, and service ranges. The three factors are basic components to describe abstract models of repository. In this article, meta data of compound knowledge are defined by being classified into the two factors. A component stands for the property about a main agent, activity unit or resource that use and create knowledge, and a context presents the context in which knowledge object are included. An agent of the compound knowledge process performs classification, registration, and pattern information management of composite knowledge, and serves as data flow and processing between compound knowledge repository and user. The agent of the compound knowledge process consists of the following functions: warning to inform data search and extraction, data collection and output for data exchange in an distributed environment, storage and registration for data, request and transmission to call for physical material wanted after search of meta data. In this article, the construction of a compound knowledge repository for recommendation system to be developed can serve a role to enhance learning productivity through real-time visualization of timely knowledge by presenting well-put various contents to users in the field of industry to occur work and learning at the same time.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.176-182
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• 2003

The use of the A* for the path search of the agent in the game map gives the computational overhead in real time game processing. To solve this problem, the route table was presented for the 2D game This route table is made in the game development phase and utilized in game playing. The route table designed for 2D game is extended for 3D game in this paper. But the memory space is required too much. This Problem can also be solved using the data compression by skipping the duplicated route table.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.406-410
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• 1998

정보통신의 모든 분야에 걸쳐 활용될 수 있는 차세대 핵심기술이라고 할 수 있는 에이전트는 자율성, 지능성, 반응성, 협동성을 갖는 독립된 프로그램으로 지식과 추론 능력을 가진다. 본 논문은 동적환경에서 환경에서 지능적인 행위와 반작용적인 행위도 가능한 혼합형 에이전트를 재난관리 에이전트 시스템에 도입 설계한다. 이를 위하여, 재난관리를 위한 에이전트를 재난 발생시 즉각적인 반응을 하는 반응 요소(reflexive component)와 플랜라이브러리에 저장된 여러 가지 사례들을 탐색해 문제를 해결하는 인지 요소(cognitive component)로 구성된 혼합형 에이전트(hybrid agent)기술을 재난관리에 적용한다. 인지요소에서 행동계획을 탐색하고, 조건에 맞는 계획을 결정하는 과정을 살펴본다. 탐색 방법은 계획-기반 탐색(plan based search)이며, 계획기의 지식 요소들은 슬롯을 가진 프레임구조를 하고 있다.

• The Journal of Information Systems
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• v.10 no.2
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• pp.5-32
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• 2001

The main goal of this research is at the development of a bundle product suggestion sub-system of an internet shopping mall for fishery products, which can reduce the search cost of user. To achieve the goal, we first study tie key factors of successful direct commerce for fishery products, and second, we design a bundle product suggestion module and its sub-module. For this, we identify the objectives of system, and write out the necessary functions of the system and models(process model, data model, dynamic model) through the analysis of user requirements. Based on the functions and models, we design user interfaces, database, processes, and knowledge base. In designing knowledge base and inferencing strategy, we consider two intelligent agent approach(optimal algorithms, heuristic rules) and suggest one more approach(case-based reasoning). The intelligent agent can be used in enhancing the suggestion of multiple fishery product simultaneously. The system analysis and design documents presented as the research results can be used to provide good guidelines to the companies who consider developing an production suggestion agents.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.439-442
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• 2016

제한된 환경에서 로봇이 동적 장애물들에 대해 능동적으로 대처하며 목표한 지점까지 도달하기 위한 알고리즘을 제안한다. 로봇은 행동기반 시스템으로 만들어져 주변 장애물들을 자율적으로 회피한다. ex-agent는 공중에서 주변 환경들을 modeling 한 뒤 cell-map을 만들어 $A^*$알고리즘을 통해 이동 경로를 설정한다. 이동 경로와 로봇의 진행방향을 비교하여 회전 방향을 조언해준다. 로봇은 ex-agent 로부터 받은 조언과 센서값들을 조율하여 장애물들을 능동적으로 회피하며 목표 위치를 찾아갈 수 있다. 실험은 시뮬레이터를 통해 이루어졌으며 장애물들에 대해 원반한 회피율을 보였다.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.159-166
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• 2012

A*algorithm is highly useful to search the shortest route to the destination in the evacuation simulation. For this reason, A*algorithm is used to evaluate the evacuation experiment by the computer simulation. However there are some problems to analyze the outcome in relation to the reality. Because all the people in the building are not well-informed of the shortest route to the exit. And they will not move to the disaster spot though it is shortest route to the exit. Therefore, evacuation simulation program based on A*algorithm raise a problem of bottleneck phenomenon and dangerous result by damage surrounding the disaster spot. The purpose of this research is to prove the necessity for dispersion evacuation simulation by Multi agent system to solve the problems of the existing evacuation simulation program based on A*algorithm.