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020 ▼a 9780438036093
035 ▼a (MiAaPQ)AAI10749752
035 ▼a (MiAaPQ)upenngdas:13135
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 004
1001 ▼a Drake, John.
24510 ▼a Planning for Non-Player Characters by Learning From Demonstration.
260 ▼a [S.l.] : ▼b University of Pennsylvania., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 139 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Adviser: Maxim Likhachev.
5021 ▼a Thesis (Ph.D.)--University of Pennsylvania, 2018.
520 ▼a In video games, state of the art non-player character (NPC) behavior generation typically depends on hard-coding NPC actions. In many game situations however, it is hard to foresee how an NPC should behave to appear intelligent or to accommodate
590 ▼a School code: 0175.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a University of Pennsylvania. ▼b Computer and Information Science.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0175
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997063 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자