CORIMP: A correlation-driven imputation approach for offline reinforcement learning with incomplete action data

No abstract is available for this paper.

• Publication year

  2026

• Venue

  Expert systems with applications

• Publication date

  2026-01-01

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1016/j.eswa.2026.131344
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• User Context Generation for Large Language Models From Mobile Sensing Data

  2025cited by this paper
• Sequence-to-Sequence Traffic Missing Data Imputation via Self-Supervised Contrastive Learning

  2025cited by this paper
• Reducing AUV Energy Consumption Through Dynamic Sensor Directions Switching via Deep Reinforcement Learning

  2025cited by this paper
• Conservative reward enhancement through the nearest neighbor integration in model-based Offline Policy Optimization

  2025cited by this paper
• Intelligent vehicle driving decision-making model based on variational AutoEncoder network and deep reinforcement learning

  2024cited by this paper
• Spatial-Temporal Interval Aware Individual Future Trajectory Prediction

  2024cited by this paper
• Offline model-based reinforcement learning with causal structured world models

  2024cited by this paper
• Automatic Environment Shaping is the Next Frontier in RL

  2024cited by this paper
• MDTGAN: Multi domain generative adversarial transfer learning network for traffic data imputation

  2024cited by this paper
• Sample-efficient reinforcement learning with knowledge-embedded hybrid model for optimal control of mining industry

  2024cited by this paper
• Meta-learning for vessel time series data imputation method recommendation

  2024cited by this paper
• Learning to Act without Actions

  2023cited by this paper
• Towards Robust Offline Reinforcement Learning under Diverse Data Corruption

  2023cited by this paper
• A missing manufacturing process data imputation framework for nonlinear dynamic soft sensor modeling and its application

  2023cited by this paper
• Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning

  2023cited by this paper
• A Customized Data Fusion Tensor Approach for Interval-Wise Missing Network Volume Imputation

  2023cited by this paper
• Towards monocular vision-based autonomous flight through deep reinforcement learning

  2022cited by this paper
• Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories

  2022cited by this paper
• Adversarially Trained Actor Critic for Offline Reinforcement Learning

  2022cited by this paper
• When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning

  2022cited by this paper
• Spatiotemporal Fracture Data Inference in Sparse Urban CrowdSensing

  2022cited by this paper
• RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning

  2022cited by this paper
• Bellman-consistent Pessimism for Offline Reinforcement Learning

  2021cited by this paper
• COMBO: Conservative Offline Model-Based Policy Optimization

  2021cited by this paper
• A Unified Collaborative Representation Learning for Neural-Network Based Recommender Systems

  2021cited by this paper
• Reinforcement learning in robotic applications: a comprehensive survey

  2021cited by this paper
• Decision Transformer: Reinforcement Learning via Sequence Modeling

  2021cited by this paper
• Offline Reinforcement Learning as One Big Sequence Modeling Problem

  2021cited by this paper
• A Minimalist Approach to Offline Reinforcement Learning

  2021cited by this paper
• MobILE: Model-Based Imitation Learning From Observation Alone

  2021cited by this paper
• Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

  2021cited by this paper
• Deep Reinforcement Learning for Autonomous Driving: A Survey

  2020cited by this paper
• Is Pessimism Provably Efficient for Offline RL?

  2020cited by this paper
• PLAS: Latent Action Space for Offline Reinforcement Learning

  2020cited by this paper
• Conservative Q-Learning for Offline Reinforcement Learning

  2020cited by this paper
• MOPO: Model-based Offline Policy Optimization

  2020cited by this paper
• MOReL : Model-Based Offline Reinforcement Learning

  2020cited by this paper
• Assessing Transferability From Simulation to Reality for Reinforcement Learning

  2019cited by this paper
• Provably Efficient Imitation Learning from Observation Alone

  2019cited by this paper
• Off-Policy Deep Reinforcement Learning without Exploration

  2018cited by this paper
• GENERATIVE ADVERSARIAL NETS

  2018cited by this paper
• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

  2018cited by this paper
• Towards autonomous behavior learning of non-player characters in games

  2016cited by this paper
• Mastering the game of Go with deep neural networks and tree search

  2016cited by this paper
• Human-level control through deep reinforcement learning

  2015cited by this paper
• Batch Reinforcement Learning

  2012cited by this paper
• Measuring and testing dependence by correlation of distances

  2007cited by this paper
• Supporting Online Material for Reducing the Dimensionality of Data with Neural Networks

  2006cited by this paper
• Missing data: our view of the state of the art.

  2002cited by this paper
• Missing value estimation methods for DNA microarrays

  2001cited by this paper
• Induction of Decision Trees

  1986cited by this paper
• Learning representations by back-propagating errors

  1986cited by this paper
• INFERENCE AND MISSING DATA

  1975cited by this paper
• Nearest neighbor pattern classification

  1967cited by this paper

• No citing papers are available for this paper.