Neurons in DRL agents are matched to short Boolean formulas over hand-defined state predicates, with anecdotal perturbation evidence that these matches reflect real behavior.
Visualization of deep reinforcement learning using grad- cam: how ai plays atari games? In 2019 IEEE conference on games (CoG), pages 1–2
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Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
Neurons in DRL agents are matched to short Boolean formulas over hand-defined state predicates, with anecdotal perturbation evidence that these matches reflect real behavior.