LDR | | 02187nam u200673 4500 |
001 | | 000000470714 |
005 | | 20220223115546 |
008 | | 220131s2021 us ||||||||||||||c||eng d |
020 | |
▼a 9798538168347 |
035 | |
▼a (MiAaPQ)AAI28650131 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 621.3 |
100 | 1 |
▼a Qiao, Zhiqian.
▼0 (orcid)0000-0001-5816-1294. |
245 | 10 |
▼a Reinforcement Learning for Behavior Planning of Autonomous Vehicles in Urban Scenarios. |
260 | |
▼a [S.l.]:
▼b Carnegie Mellon University.,
▼c 2021. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2021. |
300 | |
▼a 115 p. |
500 | |
▼a Source: Dissertations Abstracts International, Volume: 83-03, Section: B. |
500 | |
▼a Advisor: Dolan, John;Schneider, Jeff. |
502 | 1 |
▼a Thesis (Ph.D.)--Carnegie Mellon University, 2021. |
506 | |
▼a This item must not be sold to any third party vendors. |
590 | |
▼a School code: 0041. |
650 | 4 |
▼a Electrical engineering. |
650 | 4 |
▼a Simulation. |
650 | 4 |
▼a Datasets. |
650 | 4 |
▼a Control algorithms. |
650 | 4 |
▼a Teaching methods. |
650 | 4 |
▼a Success. |
650 | 4 |
▼a Experiments. |
650 | 4 |
▼a Planning. |
650 | 4 |
▼a Knowledge. |
650 | 4 |
▼a Autonomous vehicles. |
650 | 4 |
▼a Decision making. |
650 | 4 |
▼a Data collection. |
650 | 4 |
▼a Consciousness. |
650 | 4 |
▼a Core curriculum. |
650 | 4 |
▼a Heuristic. |
650 | 4 |
▼a Skills. |
650 | 4 |
▼a Computer science. |
650 | 4 |
▼a Artificial intelligence. |
650 | 4 |
▼a Automotive engineering. |
650 | 4 |
▼a Robotics. |
690 | |
▼a 0544 |
690 | |
▼a 0771 |
690 | |
▼a 0540 |
690 | |
▼a 0984 |
690 | |
▼a 0800 |
710 | 20 |
▼a Carnegie Mellon University.
▼b Electrical and Computer Engineering. |
773 | 0 |
▼t Dissertations Abstracts International
▼g 83-03B. |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0041 |
791 | |
▼a Ph.D. |
792 | |
▼a 2021 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T16053541
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 202202
▼f 2022 |
990 | |
▼a ***1012033 |
991 | |
▼a E-BOOK |