• Title/Summary/Keyword: general artificial intelligence

검색결과 267건 처리시간 0.026초

Deep Structured Learning: Architectures and Applications

  • Lee, Soowook
    • International Journal of Advanced Culture Technology
    • /
    • 제6권4호
    • /
    • pp.262-265
    • /
    • 2018
  • Deep learning, a sub-field of machine learning changing the prospects of artificial intelligence (AI) because of its recent advancements and application in various field. Deep learning deals with algorithms inspired by the structure and function of the brain called artificial neural networks. This works reviews basic architecture and recent advancement of deep structured learning. It also describes contemporary applications of deep structured learning and its advantages over the treditional learning in artificial interlligence. This study is useful for the general readers and students who are in the early stage of deep learning studies.

Design and Application of Artificial Intelligence Experience Education Class for Non-Majors (비전공자 대상 인공지능 체험교육 수업 설계 및 적용)

  • Su-Young Pi
    • Journal of Practical Engineering Education
    • /
    • 제15권2호
    • /
    • pp.529-538
    • /
    • 2023
  • At the present time when the need for universal artificial intelligence education is expanding and job changes are being made, research and discussion on artificial intelligence liberal arts education for non-majors in universities who experience artificial intelligence as part of their job is insufficient. Although artificial intelligence education courses for non-majors are being operated, they are mainly operated as theory-oriented education on the concepts and principles of artificial intelligence. In order to understand the general concept of artificial intelligence for non-majors, it is necessary to proceed with experiential learning in parallel. Therefore, this study designs artificial intelligence experiential education learning contents of difficulty that can reduce the burden of artificial intelligence classes with interest in learning by considering the characteristics of non-majors. After, we will examine the learning effect of experiential education using App Inventor and the Orange artificial intelligence platform. As a result of analysis based on the learning-related data and survey data collected through the creation of AI-related projects by teams, positive changes in the perception of the need for AI education were found, and AI literacy skills improved. It is expected that it will serve as an opportunity for instructors to lay the groundwork for designing a learning model for artificial intelligence experiential education learning.

Programming class plan for artificial intelligence education in industrial high school (공업계 고등학교 인공지능교육을 위한 프로그래밍 수업 방안)

  • Kim, Semin;Hong, Ki-Cheon;You, Kangsoo;Lee, Choong Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 한국정보통신학회 2022년도 춘계학술대회
    • /
    • pp.349-351
    • /
    • 2022
  • In this study, a programming class plan was designed for artificial intelligence education in technical high schools such as specialized high schools and Meister high schools. In elementary and middle schools or general high schools, it is not easy to secure the number of hours, so it is not easy to proceed with a lot of content and in-depth content. In addition, technical high schools have a good environment for nurturing human resources in the field of artificial intelligence. For this purpose, existing researches related to artificial intelligence education were explored, and programming classes related to artificial intelligence education were grafted into the units of the existing engineering high school programming classes.

  • PDF

Case Study on Big Data by use of Artificial Intelligence (인공지능을 활용한 빅데이터 사례분석)

  • Park, Sungbum;Lee, Sangwon;Ahn, Hyunsup;Jung, In-Hwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 한국정보통신학회 2013년도 추계학술대회
    • /
    • pp.211-213
    • /
    • 2013
  • In these days, the delusions of Big Data and apprehension about them are coming into the picture in many business fields. General techniques for preservation, analysis, and utilization of Big Data are falling short of useful techniques for the volume of fast-increasing data. However, there are some assertions that the power of analysis and prediction of Artificial Intelligence would intensify the power of Big Data analysis. This paper studies on business cases to try to graft the Artificial Intelligence technique onto Big Data analysis. We first research on various techniques of Artificial Intelligence and relations between Artificial Intelligence and Big Data. And then, we perform case studies of Big Data with using Artificial Intelligence and propose some roles of Big Data in the future.

  • PDF

Development and Application of Data Collection Education Programs for Lower Grades in Elementary School Students (초등학교 저학년을 위한 데이터 수집 교육 프로그램 개발 및 적용)

  • Yi, Seul;Ma, Daisung
    • Journal of The Korean Association of Information Education
    • /
    • 제26권1호
    • /
    • pp.45-53
    • /
    • 2022
  • The need for artificial intelligence education has emerged, and countries around the world are announcing artificial intelligence strategies. Artificial intelligence education is reflected in the main points of the 2022 revised curriculum general published in Korea. Along with this interest, programs related to artificial intelligence education are being developed, but it is difficult to find artificial intelligence programs for lower grades of elementary school. This study aims to develop a data collection education program for the lower grades of elementary school through a series of analysis-design-development-application-evaluation processes and apply it to first-grade elementary school students to verify its effectiveness. Through the developed program, it is expected that students will be able to understand and feel interested in artificial intelligence, and develop an attitude of collecting data in their daily lives through the process of searching for various types of data in their daily lives.

AI-based ICT Convergence Services to Solve Social Problems (사회문제 해결을 위한 지능화 융합 서비스)

  • Park, J.H.;Kim, M.K.;Lee, J.H.
    • Electronics and Telecommunications Trends
    • /
    • 제36권6호
    • /
    • pp.88-95
    • /
    • 2021
  • Korea will face difficult social problems including population decline and climate change in the future. Artificial intelligence (AI)-powered ICT convergence services are expected to greatly help in overcoming these social challenges. Accordingly, we have derived key promising services (AI+x) in terms of individuals, industries, and countries and identified expectations and threats perceived by the general public. These findings provide policies and research directions for promising AI-based ICT convergence services for social goods.

Enhanced MCTS Algorithm for Generating AI Agents in General Video Games (일반적인 비디오 게임의 AI 에이전트 생성을 위한 개선된 MCTS 알고리즘)

  • Oh, Pyeong;Kim, Ji-Min;Kim, Sun-Jeong;Hong, Seokmin
    • The Journal of Information Systems
    • /
    • 제25권4호
    • /
    • pp.23-36
    • /
    • 2016
  • Purpose Recently, many researchers have paid much attention to the Artificial Intelligence fields of GVGP, PCG. The paper suggests that the improved MCTS algorithm to apply for the framework can generate better AI agent. Design/methodology/approach As noted, the MCTS generate magnificent performance without an advanced training and in turn, fit applying to the field of GVGP which does not need prior knowledge. The improved and modified MCTS shows that the survival rate is increased interestingly and the search can be done in a significant way. The study was done with 2 different sets. Findings The results showed that the 10 training set which was not given any prior knowledge and the other training set which played a role as validation set generated better performance than the existed MCTS algorithm. Besed upon the results, the further study was suggested.

Frequentist and Bayesian Learning Approaches to Artificial Intelligence

  • Jun, Sunghae
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제16권2호
    • /
    • pp.111-118
    • /
    • 2016
  • Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

Univector Field Method based Multi-Agent Navigation for Pursuit Problem

  • Viet, Hoang Huu;An, Sang-Hyeok;Chung, Tae-Choong
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제12권1호
    • /
    • pp.86-93
    • /
    • 2012
  • This paper presents a new approach to solve the pursuit problem based on a univector field method. In our proposed method, a set of eight agents works together instantaneously to find suitable moving directions and follow the univector field to pursue and capture a prey agent by surrounding it from eight directions in an infinite grid-world. In addition, a set of strategies is proposed to make the pursuit problem more realistic in the real world environment. This is a general approach, and it can be extended for an environment that contains static or moving obstacles. Experimental results show that our proposed algorithm is effective for the pursuit problem.