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Offline RL

725 directly classified papers

Papers per year

Papers

Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage NIPS 2023
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples NIPS 2023
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information NIPS 2023
CLUE: Calibrated Latent Guidance for Offline Reinforcement Learning CORL 2023
Contrastive Value Learning: Implicit Models for Simple Offline RL CORL 2023
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning CORL 2023
Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score Matching CORL 2023
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning CORL 2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions CORL 2023
Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability NIPS 2023
A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories NIPS 2023
Adversarial Model for Offline Reinforcement Learning NIPS 2023
Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models NIPS 2023
Hybrid Policy Optimization from Imperfect Demonstrations NIPS 2023
An effective negotiating agent framework based on deep offline reinforcement learning UAI 2023
Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models ICML 2023
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning ICML 2023
Scalable and Safe Remediation of Defective Actions in Self-Learning Conversational Systems ACL 2023
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning ICML 2023
Learning Temporally AbstractWorld Models without Online Experimentation ICML 2023
Hyperbolic VAE via Latent Gaussian Distributions NIPS 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets NIPS 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023
Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization NIPS 2023
Safe Policy Improvement for POMDPs via Finite-State Controllers AAAI 2023