2025 Oral "reinforcement learning agents" Papers

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Conference

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Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments

Riley Simmons-Edler, Ryan Badman, Felix Berg et al.

NEURIPS 2025oralarXiv:2506.06981
3
citations

Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning

Jiuqi Wang, Ethan Blaser, Hadi Daneshmand et al.

ICLR 2025oralarXiv:2405.13861
14
citations