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Found 4 papers, 1 papers with code
Explaining Learned Reward Functions with Counterfactual Trajectories
Finally, we measure how informative the generated explanations are to a proxy-human model by training it on CTEs.
ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility
We present ReproducedPapers. org: an open online repository for teaching and structuring machine learning reproducibility.
Maximizing Information Gain in Partially Observable Environments via Prediction Reward
Information gathering in a partially observable environment can be formulated as a reinforcement learning (RL), problem where the reward depends on the agent's uncertainty.
Bayesian Reinforcement Learning in Factored POMDPs
Bayesian approaches provide a principled solution to the exploration-exploitation trade-off in Reinforcement Learning.
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