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cs.LG2026
Density-Guided Bootstrap Boundaries for Latent World-Model Reinforcement Learning
Shashank Gupta, Pilhwa Lee
Latent world models allow reinforcement learning agents to learn policies from imagined trajectories, yet determining the optimal depth of model reliance remains a fundamental chal…
cs.LG2025
Meta-reinforcement learning with minimum attention
Shashank Gupta, Pilhwa Lee
Minimum attention applies the least action principle in changes of control concerning state and time, first proposed by Brockett. The involved regularization is highly relevant in…