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cs.LG2026
Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
Mahsa Bastankhah, Sophie Broderick, Benjamin Eysenbach
In many practical reinforcement learning environments, observations are far higher-dimensional than the variables that matter for control. In this work, we ask: can we learn repres…
cs.LG2026
Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
Alireza Modirshanechi, Benjamin Eysenbach, Peter Dayan +1
Unsupervised pretraining has driven empirical advances in goal-conditioned reinforcement learning (GCRL), but its theoretical foundations remain poorly understood. In particular, a…