• Title/Summary/Keyword: 알파고

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과학상식 - 인간과 기계 사이의 경계가 무너진다 우리의 선택은?

  • U, A-Yeong
    • Korea Petroleum Association Journal
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    • s.300
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    • pp.40-43
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    • 2016
  • 지난 3월, 서울에서 세기의 대결이 펼쳐졌다. 구글의 '알파고'와 이세돌 9단의 바둑 대결이 벌어진 것. 결과는 4대 1로 알파고의 승리였다. 인간이 기계에 졌다며 침통해 하는 반응이 쏟아지는 한편, 인공지능에 대한 국민의 관심이 최고조로 달아올랐다. '알파고 쇼크' 이후 인공지능으로 대표되는 최첨단 기술의 다음 단계는 무엇이며, 우리는 과연 어떤 미래를 맞이하게 될 것인지에 대해 갑론을박이 벌어졌다.

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AlphaGo Case Study: On the Social Nature of Artificial Intelligence (알파고 사례 연구: 인공지능의 사회적 성격)

  • Kim, Ji Yeon
    • Journal of Science and Technology Studies
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    • v.17 no.1
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    • pp.5-39
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    • 2017
  • In March 2016, the computer Go program, AlphaGo, defeated Sedol Lee, a Korean professional Go player of 9-dan rank. This victory by AlphaGo shows the rise in popularity of artificial intelligence (AI). Not only was this game a testament to machine performance, it was the type of game that extended the Turing test. When the interrogator cannot differentiate between human being and machine, the machine has passed the test. This article examines the interactions between AI and human beings and studies the social nature of intelligence through the AlphaGo case. Collins insists that knowledge or intelligence is social and embodied, and the interrogators in the Turing test can identify the difference between native members and non-members through their knowledge only. Applying this concept, AlphaGo, as subject A of this test, fulfilled its role of stirring up the classical "truth of human." Meanwhile, Lee as subject B, played to speak the truth by revealing his own qualities. Here, it is also important role that interrogators judge what it is. Many spectators, as interrogators, have intervened to confirm the border between human beings and machines by using their embodied and social knowledge.

Comparison of Fuzzy Implication Operators by means of a Local Path-Planning of AUVs (자율수중운동체의 상세경로설정기법을 위한 퍼지조건연산자의 비교)

  • 이영일;김용기
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.140-143
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    • 2002
  • 본 논문에서는 자율수중운동체(AUV, Autonomous Underwater Vehicle)의 실시간 충돌회피에 적용되는 휴리스틱 탐색기법에 적합한 퍼지조건연산자와 알파절단(aleph-cut)의 선택에 관해 논한다. 퍼지조건연산자와 알파절단은 두 퍼지관계에서 새로운 퍼지관계를 생성시키는 퍼지삼각논리곱의 연산에 적용되는데 이것은 휴리스틱탐색기법의 이론적 기반이 된다. 본 논문은 평가함수를 이용한 새로운 휴리스틱탐색기법을 설계하고, 이에 가장 적합한 퍼지조건연산자와 알파절단을 제안한다. 제안된 퍼지조건연산자와 알파절단의 검증을 위해 경로경비와 합리적인 경로를 생성하는 알파절단의 개수 관점에서 모든 경우의 퍼지조건연산자와 알파절단에 대해 시뮬레이션 한다. .

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Ensure intellectual property rights for 3D pringting 3D modeling design (딥러닝 인공지능을 활용한 사물인터넷 비즈니스 모델 설계)

  • Lee, Yong-keu;Park, Dae-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.351-354
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    • 2016
  • The competition of Go between AlphaGo and Lee Sedol attracted global interest leading AlphaGo to victory. The core function of AlphaGo is deep-learning system, studying by computer itself. Afterwards, the utilization of deep-learning system using artificial intelligence is said to be verified. Recently, the government passed the loT Act and developing its business model to promote loT. This study is on analyzing IoT business environment using deep-learning AI and constructing specialized business models.

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Research on optimal port cargo vehicle arrival scheduling system using Monte Carlo simulation, AlphaGo Zero, and Bayes' theorem (몬테카를로 시뮬레이션, 알파고 제로, 베이즈 정리를 이용한 최적의 항만 화물차 입항 스케줄링 시스템에 대한 연구)

  • Min-Gyeong Kim;Sua Park;Hae-Young Lee;Na-Young Kim;Sang-Oh Yoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.1096-1097
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    • 2023
  • 본 연구에서는 항만 교통 혼잡 문제를 해결하기 위해 최적화와 관련된 요소와 트럭 운전기사와 터미널 사이의 협상과 관련된 요소를 새로운 방식으로 고려한 중장기 및 실시간 스케줄링 모델을 제시한다. 중장기 스케줄링 모델은 몬테카를로 시뮬레이션, 실시간 스케줄링 모델은 알파고 제로의 원리와 베이즈 정리를 이용하여 구현했다. 실험 결과 제시된 알파고 제로를 이용한 실시간 스케줄링 시스템이 화물차 평균 지연시간을 30분에서 4분으로 대폭 줄여 지연 시간을 최소화하는 것을 입증했다. 실험 관련 코드는 다음 주소에서 확인할 수 있다 : https://github.com/yulleta/Application_of_AlphaGo-Zero_to_port_arrival_scheduling

Topophilia Convergence Science Education for Enhancing Learning Capabilities in the Age of Artificial Intelligence Based on the Case of Challenge Match Lee Sedol and AlphaGo (알파고와 이세돌의 챌린지 매치에서 분석된 인공지능 시대의 학습자 역량을 위한 토포필리아 융합과학 교육)

  • Yoon, Ma-Byong;Lee, Jong-Hak;Baek, Je-Eun
    • Journal of the Korea Convergence Society
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    • v.7 no.4
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    • pp.123-131
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    • 2016
  • In this paper, we discussed learner's capability enhancement education suitable for the age of artificial intelligence (AI) using game analysis and archival research based on the 2016 Google Deepmind Challenge match between AI that possessed the finest deep neural networks and the master Baduk player that represented the best of the human minds. AlphaGo was a brilliant move that transcended the conventional wisdom of Baduk and introduced a new paradigm of Baduk. Lee Sedol defeated AlphaGo via the 'divine move and Great idea' that even AlphaGo could not have calculated. This was the triumph of human intuition and insights, which are deeply embedded in human nature as well as human courage and strength. Convergence science education that cultivates student abilities that can help them control machines in the age of AI must be in the direction of developing diverse human insights and positive spirits embedded in human nature not possessed by AI via implementing hearts-on experience and topophilia education obtained from the nature.

Review of the Gross Alpha for Characterization of Radioactive Waste (방사성폐기물 특성평가를 위한 전알파 분석법 고찰)

  • Kim, Hyuncheol;Lim, Jong-Myoung;Jang, Mee;Park, Ji-Young
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.18 no.2_spc
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    • pp.227-235
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    • 2020
  • In this study, we discussed the limitations of gross alpha measurements for the characterization of radioactive wastes produced in nuclear facilities through experimental tests and Monte Carlo N-particle transport simulations. The determination of gross alpha is essential for the disposal of radioactive waste produced in nuclear facilities in Korea. The measurements of gross alpha are easy to perform and yield rapid analytical results, but it cannot be used for quantitative analysis. The error of counting efficiency for gross alpha with various masses of the deposit on planchets using KCl and 241Am was determined. The relative deviation of the counting efficiency in samples having the same mass was 20%. Uranium was extracted from the soil through acid leaching and extraction chromatography, and the concentration of U determined by inductively coupled plasma-mass spectrometry (ICP-MS) was compared with the results for gross alpha. The gross alpha was underestimated by 50% compared to the U concentration by ICP-MS. The counting efficiency depended on the energy from the alpha emitters, which differed by up to three times in determination of the counting efficiency depending on the kinds of alpha radionuclides of interest. Therefore, the gross alpha is not compatible with the sum of radioactivity for each alpha emitter and is suitable as a screening method.