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Eliciting and Aggregating Information for Better Decision Making
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Eliciting and Aggregating Information for Better Decision Making. |
| 개인저자 | Freeman, Rupert. |
| 단체저자명 | Duke University. Computer Science. |
| 발행사항 | [S.l.]: Duke University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 276 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-02B(E). Dissertation Abstract International |
| ISBN | 9780438376557 |
| 학위논문주기 | Thesis (Ph.D.)--Duke University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B.
Adviser: Vincent Conitzer. |
| 요약 | In this thesis, we consider two classes of problems where algorithms are increasingly used to make, or assist in making, a wide range of decisions. The first class of problems we consider is the allocation of jointly owned resources among a grou |
| 요약 | In the first part of the thesis, we consider shared resource allocation, where we relax two common assumptions in the fair divison literature. Firstly, we relax the assumption that goods are private, meaning that they must be allocated to only a |
| 요약 | In the second part of the thesis, we consider the design of mechanisms for forecasting. We first consider a tradeoff between several desirable properties for wagering mechanisms, showing that the properties of Pareto efficiency, incentive compat |
| 일반주제명 | Artificial intelligence. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
