Search Results for author: Yongsik Lee

Found 4 papers, 2 papers with code

Preference Alignment with Flow Matching

1 code implementation30 May 2024 Minu Kim, Yongsik Lee, Sehyeok Kang, Jihwan Oh, Song Chong, Se-Young Yun

We present Preference Flow Matching (PFM), a new framework for preference-based reinforcement learning (PbRL) that streamlines the integration of preferences into an arbitrary class of pre-trained models.

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions

1 code implementation5 Jul 2022 Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong, Se-Young Yun

This challenge, on the other hand, is interested in the exploration capability of MARL algorithms to efficiently learn implicit multi-stage tasks and environmental factors as well as micro-control.

SMAC+

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