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cs.LG2025
Attention Trajectories as a Diagnostic Axis for Deep Reinforcement Learning
Charlotte Beylier, Hannah Selder, Arthur Fleig +2
The emergence and evolution of feature reliance in deep reinforcement learning agents remain poorly understood. Here, we introduce a methodological framework for analyzing the lear…
cs.LG2024
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics
Charlotte Beylier, Simon M. Hofmann, Nico Scherf
The learning process of a reinforcement learning (RL) agent remains poorly understood beyond the mathematical formulation of its learning algorithm. To address this gap, we introdu…