The Quest for Autonomous Scientific Discoveries with Artificial Scientists- [electronic resource]
The Quest for Autonomous Scientific Discoveries with Artificial Scientists- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101926
- ISBN
- 9798380856201
- DDC
- 501
- 서명/저자
- The Quest for Autonomous Scientific Discoveries with Artificial Scientists - [electronic resource]
- 발행사항
- [S.l.]: : Indiana University., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(197 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
- 주기사항
- Advisor: Hagar, Amit.
- 학위논문주기
- Thesis (Ph.D.)--Indiana University, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약The dissertation delves into the dynamic realm of AI capabilities, focusing on its potential for autonomous scientific discovery. At its core, it addresses the fundamental question of whether AI can autonomously make scientific discovery. A significant aspect of the study involves proposing a set of formalized tests to assess AI's capacity as an "artificial scientist." These tests serve as indicators of AI's ability to engage in independent scientific discovery. Additionally, a classification system is introduced to categorize artificial scientists into four distinct tiers, based on their adaptability and autonomy. These tiers are ranked as general self-initiated, narrow self-initiated, general non-self-initiated, and narrow non-self-initiated. This dissertation argues that, with existing AI paradigms and techniques, achieving the fourth tier of artificial scientists, capable of autonomous scientific discovery in certain domains under human guidance, is already practically attainable. However, reaching the highest tier, characterized by comprehensive adaptability and autonomy, may require a pioneering approach that seamlessly merges natural intelligence with artificial intelligence. Moreover, an exploration of the philosophy of science itself becomes imperative in attaining this pinnacle of AI's potential.
- 일반주제명
- Philosophy of science.
- 일반주제명
- Systems science.
- 일반주제명
- Robotics.
- 키워드
- Robot scientists
- 키워드
- Adaptability
- 기타저자
- Indiana University History and Philosophy of Science
- 기본자료저록
- Dissertations Abstracts International. 85-05B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520240214101926
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■020 ▼a9798380856201
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a501
■1001 ▼aRuangsakul, Siwarak.▼0(orcid)0009-0002-5824-5791
■24510▼aThe Quest for Autonomous Scientific Discoveries with Artificial Scientists▼h[electronic resource]
■260 ▼a[S.l.]:▼bIndiana University. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(197 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-05, Section: B.
■500 ▼aAdvisor: Hagar, Amit.
■5021 ▼aThesis (Ph.D.)--Indiana University, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aThe dissertation delves into the dynamic realm of AI capabilities, focusing on its potential for autonomous scientific discovery. At its core, it addresses the fundamental question of whether AI can autonomously make scientific discovery. A significant aspect of the study involves proposing a set of formalized tests to assess AI's capacity as an "artificial scientist." These tests serve as indicators of AI's ability to engage in independent scientific discovery. Additionally, a classification system is introduced to categorize artificial scientists into four distinct tiers, based on their adaptability and autonomy. These tiers are ranked as general self-initiated, narrow self-initiated, general non-self-initiated, and narrow non-self-initiated. This dissertation argues that, with existing AI paradigms and techniques, achieving the fourth tier of artificial scientists, capable of autonomous scientific discovery in certain domains under human guidance, is already practically attainable. However, reaching the highest tier, characterized by comprehensive adaptability and autonomy, may require a pioneering approach that seamlessly merges natural intelligence with artificial intelligence. Moreover, an exploration of the philosophy of science itself becomes imperative in attaining this pinnacle of AI's potential.
■590 ▼aSchool code: 0093.
■650 4▼aPhilosophy of science.
■650 4▼aSystems science.
■650 4▼aRobotics.
■653 ▼aArtificial scientists
■653 ▼aRobot scientists
■653 ▼aScientific discovery
■653 ▼aAutonomous scientific discovery
■653 ▼aAdaptability
■690 ▼a0402
■690 ▼a0800
■690 ▼a0771
■690 ▼a0790
■71020▼aIndiana University▼bHistory and Philosophy of Science.
■7730 ▼tDissertations Abstracts International▼g85-05B.
■773 ▼tDissertation Abstract International
■790 ▼a0093
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16935386▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
