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20212026
most citedRAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning

19 citations · 37 across the 22 of their papers we have counts for

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cs.LG2026

Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies

Alex Schutz, Nick Hawes, Victor-Alexandru Darvariu

Graph-based world models have recently emerged as a means of learning transitions over relational state representations. However, existing approaches are largely limited to fixed-t…

cs.LG2026

Improving Regret Approximation for Unsupervised Dynamic Environment Generation

Harry Mead, Bruno Lacerda, Jakob Foerster +1

Unsupervised Environment Design (UED) seeks to automatically generate training curricula for reinforcement learning (RL) agents, with the goal of improving generalisation and zero-…