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Found 6 papers, 1 papers with code
Understanding and Leveraging Overparameterization in Recursive Value Estimation
To better understand the utility of deep models in RL we present an analysis of recursive value estimation using overparameterized linear representations that provides useful, transferable findings.
Joint Shapley values: a measure of joint feature importance
The Shapley value is one of the most widely used measures of feature importance partly as it measures a feature's average effect on a model's prediction.
A maximum-entropy approach to off-policy evaluation in average-reward MDPs
This work focuses on off-policy evaluation (OPE) with function approximation in infinite-horizon undiscounted Markov decision processes (MDPs).
RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real
However, this sort of translation is typically task-agnostic, in that the translated images may not preserve all features that are relevant to the task.
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making
We investigate batch policy optimization for cost-sensitive classification and contextual bandits---two related tasks that obviate exploration but require generalizing from observed rewards to action selections in unseen contexts.
Off-Policy Evaluation via Off-Policy Classification
However, for high-dimensional observations, such as images, models of the environment can be difficult to fit and value-based methods can make IS hard to use or even ill-conditioned, especially when dealing with continuous action spaces.
