• Title/Summary/Keyword: Intelligent Agent

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지능형 에이전트(Intelligent Agent)의 동향

  • Ju, Seok-Jin
    • 정보화사회
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    • pp.30-36
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    • 1997
  • 지능형 에이전트는 사용자의 일상적인 일들을 대신해주거나 반복적인 일들을 사람보다 빨리 처리해준다. 즉, 사용자의 요구를 받아 온라인 쇼핑에서 최저가가격의 검토, 전자우편의 수발신, 사용자가 휴가중인 경우에 일정의 조정등 사용자의 입장에서 적극적인 업무 처리를 도와준다.

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Applying Intelligent Agent and Petri Net Modeling Technology to ERT Maintenance (지능형 에이전트와 페트리네트 모형화 기술을 활용한 ERP 유지보수 방법론)

  • 권오병;이재준
    • Journal of Information Technology Application
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    • v.2 no.1
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    • pp.113-137
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    • 2000
  • Even though there is no doubt that ERP(Enterprise Resource Planing) system is a prevailing solution for integrating corporate information, many companies still hesitate adopting ERP system because of a great deal of cost including maintenance cost. In special, unless consulting knowledge that is infused into process reengineering phase or adequately embedded in customized ERP system is upgraded on time, then we cannot guarantee the optimality of system performance. Hence, this paper aims to construct an ERP system that adapts itself to environmental changes that are issued by database and users. To do so, we adopt intelligent agent technology and Petri net theory. The agents autonomously cooperate each other to investigate databases and to find any exceptional changes and analyze how the changes will affect ERP performance. The dynamics of the agents are represented as Petri nets. The newly proposed ERP system is to make corresponding BPR processes maintain optimality. To show the feasibility of the proposed ERP maintenance system, logistics component is described as an illustrative example.

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Exploration of User Experience Research Method with Big Data Analysis : Focusing on the Online Review Analysis of Echo (빅데이터 분석을 활용한 사용자 경험 평가 방법론 탐색 : 아마존 에코에 대한 온라인 리뷰 분석을 중심으로)

  • Hwang, Hae Jeong;Shim, Hye Rin;Choi, Junho
    • The Journal of the Korea Contents Association
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    • v.16 no.8
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    • pp.517-528
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    • 2016
  • This study attempted to explore and examine a new user experience (UX) research method for IoT products which are becoming widely used but lack practical user research. While user experience research has been traditionally opted for survey or observation methods, this paper utilized big data analysis method for user online reviews on an intelligent agent IoT product, Amazon's Echo. The results of topic modelling analysis extracted user experience elements such as features, conversational interaction, and updates. In addition, regression analysis showed that the topic of updates was the most influential determinant of user satisfaction. The main implication of this study is the new introduction of big data analysis method into the user experience research for the intelligent agent IoT products.

Personalized Wire and Wireless News Retrieval System Using Intelligent Agent (지능형 에이전트를 이용한 개인화된 유.무선 뉴스 검색 시스템)

  • Han, Seon-Mi;Woo, Jin-Woon
    • The KIPS Transactions:PartB
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    • v.8B no.6
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    • pp.609-616
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    • 2001
  • Today, as the Internet is popularized, information and news retrieval are generalized. However due to the tremendous amount and variety of information, many users appeal the difficulties of information retrieval. Thus in this paper, we propose a news retrieval system, which filters news articles using an intelligent agent with the learning ability of BPN (back propagation neural network). This system also uses a profile to accomodate the personalized news retrieval. This system consists of two major agents, collection agent and learning agent. The collection agent gathers the articles from several news sites, analyzes them, and stores into a database. The learning agent builds the BPN based on the personalized data. In addition, considering the popularity of the wireless internet due to the rapid development of communication technologies, we made this system provide the service through the wireless internet.

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Architecture and Path-Finding Behavior of An Intelligent Agent Deploying within 3D Virtual Environment (3차원 가상환경에서 동작하는 지능형 에이전트의 구조와 경로 찾기 행위)

  • Kim, In-Cheol;Lee, Jae-Ho
    • The KIPS Transactions:PartB
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    • v.10B no.1
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    • pp.1-12
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    • 2003
  • In this paper, we Introduce the Unreal Tournament (UT) game and the Gamebots system. The former it a well-known 3D first-person action game and the latter is an intelligent agent research testbed based on UT And then we explain the design and implementation of KGBot, which is an intelligent non-player character deploying effectively within the 3D virtual environment provided by UT and the Gamebots system. KGBot is a bot client within the Gamebots System. KGBot accomplishes its own task to find out and dominate several domination points pro-located on the complex surface map of 3D virtual environment KGBot adopts UM-PRS as its control engine, which is a general BDI agent architecture. KGBot contains a hierarchical knowledge base representing its complex behaviors in multiple layers. In this paper, we explain details of KGBot's Intelligent behaviors, tuck af locating the hidden domination points by exploring the unknown world effectively. constructing a path map by collecting the waypoints and paths distributed over the world, and finding an optimal path to certain destination based on this path graph. Finally we analyze the performance of KGBot exploring strategy and control engine through some experiments on different 3D maps.

Cognitive Approach for Building Intelligent Agent (지능 에이전트 구현의 인지적 접근)

  • Tae Kang-Soo
    • Journal of Internet Computing and Services
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    • v.5 no.2
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    • pp.97-105
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    • 2004
  • The reason that an intelligent agent cannot understand the representation of its own perception or activity is caused by the traditional syntactic approach that translates a semantic feature into a simulated string, To implement an autonomously learning intelligent agent, Cohen introduces a experimentally semantic approach that the system learns a contentful representation of physical schema from physically interacting with environment using its own sensors and effectors. We propose that negation is a meta-level schema that enables an agent to recognize its own physical schema, To improve the planner's efficiency, Graphplan introduces the control rule that manipulates the inconsistency between planning operators, but it cannot cognitively understand negation and suffers from redundancy problem. By introducing a negative function not, IPP solves the problem, but its approach is still syntactic and is inefficient in terms of time and space. In this paper, we propose that, to represent a negative fact, a positive atom, which is called opposite concept, is a very efficient technique for implementing an cognitive agent, and demonstrate some empirical results supporting the hypothesis.

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A Development of Intelligent Simulation Tools based on Multi-agent (멀티 에이전트 기반의 지능형 시뮬레이션 도구의 개발)

  • Woo, Chong-Woo;Kim, Dae-Ryung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.6
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    • pp.21-30
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    • 2007
  • Simulation means modeling structures or behaviors of the various objects, and experimenting them on the computer system. And the major approaches are DEVS(Discrete Event Systems Specification). Petri-net or Automata and so on. But, the simulation problems are getting more complex or complicated these days, so that an intelligent agent-based is being studied. In this paper, we are describing an intelligent agent-based simulation tool, which can supports the simulation experiment more efficiently. The significances of our system can be described as follows. First, the system can provide some AI algorithms through the system libraries. Second, the system supports simple method of designing the simulation model, since it's been built under the Finite State Machine (FSM) structure. And finally, the system acts as a simulation framework by supporting user not only the simulation engine, but also user-friendly tools, such as modeler scriptor and simulator. The system mainly consists of main simulation engine, utility tools, and some other assist tools, and it is tested and showed some efficient results in the three different problems.

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Design and Implementation of Agent Systems based on Case Markup Language for e-Leaning (e-Learning을 위한 사례 마크업 언어 기반 에이전트 시스템의 설계 및 구현 :사례 기반 학습자 모델을 중심으로)

  • 한선관;윤정섭;조근식
    • The Journal of Society for e-Business Studies
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    • v.6 no.3
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    • pp.63-80
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    • 2001
  • The construction of the students knowledge in e-Learning systems, namely the student modeling, is a core component used to develop e-Learning systems. However, existing e-Learning systems have many problems to share the knowledge in a heterogeneous student model and a distributed knowledge base. Because the methods of the knowledge representation are different in each e-Learning systems, the accumulated knowledge cannot be used or shared without a great deal of difficulty. In order to share this knowledge, existing systems must reconstruct the knowledge bases. Consequently, we propose a new a Case Markup Language based on XML in order to overcome these problems. A distributed e-Learning systems fan have the advantage of easily sharing and managing the heterogeneous knowledge base proposed by CaseML. Moreover students can generate and share a case knowledge to use the communication protocol of agents. In this paper, we have designed and developed a CaseML by using a knowledge markup language. Furthermore, in order to construct an intelligent e-Learning systems, we have done our research based on the design and development of the intelligent agent system by using CaseML.

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