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Found 2 papers, 2 papers with code
Explaining Reinforcement Learning Policies through Counterfactual Trajectories
In order for humans to confidently decide where to employ RL agents for real-world tasks, a human developer must validate that the agent will perform well at test-time.
Neural Parameter Allocation Search
We introduce Neural Parameter Allocation Search (NPAS), a novel task where the goal is to train a neural network given an arbitrary, fixed parameter budget.
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