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![강화 학습 기반 NPC AI
[B&S 무한의 탑 AI 활용 사례]
Inven Game Conference
NCSOFT
AI Center / Game AI팀
이경종](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-1-2048.jpg?cb=1667510969)
![Chapter [1]
Overview
Inven Game Conference](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-3-2048.jpg?cb=1667510969)
![1
Overview
What is the Game AI?
[ 최근 동향 ]
• Decision Making: Machine Learning / MCTS based AI
• Procedural Content Generat...](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-5-2048.jpg?cb=1667510969)
![1
Overview
B&S 무한의 탑 AI
필요한 AI는 무엇인가?
HumanAI
1:1 PvP
[ Input ]
• 현재 상황 (State)
• 직업별 사용 가능한 스킬
(Action, 최대 50개)
• 총 9개 직업...](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-8-2048.jpg?cb=1667510969)
![Chapter [2]
강화 학습 기반 AI
Inven Game Conference](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-9-2048.jpg?cb=1667510969)
![2
강화 학습 기반 AI
강화 학습이란? [1/2]
•
•
Learning Without a Teacher
10](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-10-2048.jpg?cb=1667510969)
![2
강화 학습 기반 AI
강화 학습이란? [2/2]
• Task: 로봇 팔의 움직임을 제어하여 팬케익 뒤집기
•
•
팬케익 뒤집기 로봇 Example
Trial 성공, 실패 Feedback 관절에 ...](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-11-2048.jpg?cb=1667510969)
![Chapter [3]
강화 학습 시스템
Inven Game Conference](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-20-2048.jpg?cb=1667510969)
![Chapter [4]
향후 R&D 방향
Inven Game Conference](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-26-2048.jpg?cb=1667510969)
![감사합니다
[AI Center / Game AI팀 팀장]
이 경 종](https://image.slidesharecdn.com/igcnpcai20161007-161010052405/75/IGC-NPC-AI-29-2048.jpg?cb=1667510969)