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cs.LG2025
DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
Changyeon Kim, Haeone Lee, Younggyo Seo +2
Offline reinforcement learning (RL) presents an attractive paradigm for training intelligent agents without expensive online interactions. However, current approaches still struggl…
cs.LG2025
VLM Q-Learning: Aligning Vision-Language Models for Interactive Decision-Making
Jake Grigsby, Yuke Zhu, Michael Ryoo +1
Recent research looks to harness the general knowledge and reasoning of large language models (LLMs) into agents that accomplish user-specified goals in interactive environments. V…
cs.LG2025
Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers
Jake Grigsby, Yuqi Xie, Justin Sasek +2
Competitive Pokémon Singles (CPS) is a popular strategy game where players learn to exploit their opponent based on imperfect information in battles that can last more than one hun…