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Found 7 papers, 2 papers with code
Batch Reinforcement Learning with Hyperparameter Gradients
We consider the batch reinforcement learning problem where the agent needs to learn only from a fixed batch of data, without further interaction with the environment.
Offline Imitation Learning by Controlling the Effective Planning Horizon
In offline imitation learning (IL), we generally assume only a handful of expert trajectories and a supplementary offline dataset from suboptimal behaviors to learn the expert policy.
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions
We consider local kernel metric learning for off-policy evaluation (OPE) of deterministic policies in contextual bandits with continuous action spaces.
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
We consider the offline reinforcement learning (RL) setting where the agent aims to optimize the policy solely from the data without further environment interactions.
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Safe and reliable electricity transmission in power grids is crucial for modern society.
Representation Balancing Offline Model-based Reinforcement Learning
We present a new objective for model learning motivated by recent advances in the estimation of stationary distribution corrections.
