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Computational Modeling of Behavior and Neural Mechanisms of Decision-Making Using Reinforcement Learning Theory
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Computational Modeling of Behavior and Neural Mechanisms of Decision-Making Using Reinforcement Learning Theory. |
| 개인저자 | Pietras, Bradley William. |
| 단체저자명 | University of Maryland, Baltimore. Neuroscience. |
| 발행사항 | [S.l.]: University of Maryland, Baltimore., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 197 p. |
| 기본자료 저록 | Dissertations Abstracts International 80-12B. Dissertation Abstract International |
| ISBN | 9781392301432 |
| 학위논문주기 | Thesis (Ph.D.)--University of Maryland, Baltimore, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 80-12, Section: B.
Publisher info.: Dissertation/Thesis. Advisor: Schoenbaum, Geoffrey |
| 이용제한사항 | This item must not be added to any third party search indexes.This item must not be sold to any third party vendors. |
| 요약 | In the study of learning and decision-making in animals and humans, the field of Reinforcement Learning (RL) offers powerful ideas and tools for exploring the control mechanisms that underlie behavior.In this dissertation, we use RL to examine the questions of (i) how rats represent information about a complex, changing, task |
| 일반주제명 | Neurosciences. Artificial intelligence. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
