| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000332702 |
| 005 | | 20241204153853 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438376557 |
| 035 | |
▼a (MiAaPQ)AAI10811769 |
| 035 | |
▼a (MiAaPQ)duke:14738 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 001.5 |
| 100 | 1 |
▼a Freeman, Rupert. |
| 245 | 10 |
▼a Eliciting and Aggregating Information for Better Decision Making. |
| 260 | |
▼a [S.l.] :
▼b Duke University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 276 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. |
| 500 | |
▼a Adviser: Vincent Conitzer. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Duke University, 2018. |
| 520 | |
▼a 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 |
| 520 | |
▼a 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 |
| 520 | |
▼a 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 |
| 590 | |
▼a School code: 0066. |
| 650 | 4 |
▼a Artificial intelligence. |
| 690 | |
▼a 0800 |
| 710 | 20 |
▼a Duke University.
▼b Computer Science. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0066 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997999
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |