Hello, I am Jihwan Oh. My research area was Multi Agent Deep Reinforcement Learning until 2022. Thesedays, I have centered on communication among agents with Generative models in various domain.

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Publications

C: Conference, W: Workshop, J: Journal, P: Preprint, D: Domestic.
* : Equal Contribution

[J1] The StarCraft Multi-Agent Exploration Challenges: Learning Multi-Stage Tasks and Environmental Factors without Precise Reward Functions
Mingyu Kim*, Jihwan Oh* Yongsik Lee, Joonkee Kim, Seonghwan Kim, Song Chong, Se-Young Yun
IEEE Access’23 [Paper]

[C1] Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning
Jihwan Oh*, Joonkee Kim*, Minchan Jeong, Se-Young Yun
AAMAS’23 [Paper]

[W2] Risk Perspective Exploration in Distributional Reinforcement Learning
Jihwan Oh, Joonkee Kim, Se-Young Yun
AI for Agent Based Modelling Workshop at ICML’22 [Paper]

[W1] Real-time and Explainable Detection of Epidemics with Global News Data
Sungnyun Kim, Jaewoo Shin, Seongha Eom, Jihwan Oh, Se-Young Yun Workshop on Healthcare AI and COVID-19, ICML’22 [Paper]

[D2] Risk Scheduling-based Optimistic Exploration for Distributional Reinforcement Learning
Jihwan Oh, Joonkee Kim, Se-Young Yun
KCC’23 [Paper]

[D1] The Unified Framework for Efficient Deep Learning Computer Vision Model
Seungjoon Park, Jihwan Oh, Taehyun Kim, Se-Young Yun
KIISE’21

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Patent

[1] 전장 상황에서의 방책 추천을 위한 강화학습 방법 및 시스템, 이를 위한 컴퓨팅 장치
KOR patent number: 10-2022-0171478

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Education

[KAIST], Ph.D student in Graduate school of AI/ Seoul, South Korea/ 2024~ under professor Se-Young Yun
[KAIST], M.S. in Graduate school of AI/ Seoul, South Korea/ Feb 2023 under professor Se-Young Yun
[KMA], B.S. in Economics/ Seoul, South Korea/ Feb 2016