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Found 6 papers, 1 papers with code
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Interpretability and transparency are essential for incorporating causal effect models from observational data into policy decision-making.
Suboptimal and trait-like reinforcement learning strategies correlate with midbrain encoding of prediction errors
During probabilistic learning organisms often apply a sub-optimal "probability-matching" strategy, where selection rates match reward probabilities, rather than engaging in the optimal "maximization" strategy, where the option with the highest reward probability is always selected.
Replay For Safety
Experience replay \citep{lin1993reinforcement, mnih2015human} is a widely used technique to achieve efficient use of data and improved performance in RL algorithms.
Convergence Results For Q-Learning With Experience Replay
A commonly used heuristic in RL is experience replay (e. g.~\citet{lin1993reinforcement, mnih2015human}), in which a learner stores and re-uses past trajectories as if they were sampled online.
Online Learning with Local Permutations and Delayed Feedback
In this paper, we consider the applicability of this setting to convex online learning with delayed feedback, in which the feedback on the prediction made in round $t$ arrives with some delay $\tau$.
Multi-Player Bandits -- a Musical Chairs Approach
We consider a variant of the stochastic multi-armed bandit problem, where multiple players simultaneously choose from the same set of arms and may collide, receiving no reward.
