mlsanityData to 14 Oct 2026

Completion-Aware Cross-Fidelity Offline-to-Online Reinforcement Learning for Multi-Line Bus Holding

arXiv 2609.39868 ↗First posted 30 Sep 2026cs.AI cs.LGcited by 0

New in Offline RL and imitation learning from data; no direction yet. Offline RL and imitation learning from data

Abstract (arXiv)

Exploratory reinforcement learning (RL) on an operating bus fleet is impractical,while policies trained only from historical data cannot acquire new experience. Hybrid Offline-and-Online (H2O) RL combines fixed target replay with simulator interaction, but the inexpensive online simulator can differ from the target in transition and event-duration dynamics. We study this cross-fidelity problem for multi-line bus holding and address a failure mode in which lower generalized passenger time coexists with incomplete passenger journeys.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 23 references that are in the map. First posted on arXiv 30 Sep 2026.

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12 of 23 references.

References · 12

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  2. 2020Conservative Q-Learning for Offline Reinforcement Learningcited by 1,809
  3. 2021Offline Reinforcement Learning with Implicit Q-Learningcited by 1,293
  4. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,240
  5. 2023Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuningcited by 237
  6. 2021Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemblecited by 214
  7. 2020Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifierscited by 97
  8. 2024Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Datacited by 63
  9. 2022When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learningcited by 60
  10. 2023H2O+: An Improved Framework for Hybrid Offline-and-Online RL with Dynamics Gapscited by 17
  11. 2021Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learningcited by 7
  12. 2025Coordinating Ride-Pooling with Public Transit using Reward-Guided Conservative Q-Learning: An Offline Training and Online Fine-Tuning Reinforcement Learning Frameworkcited by 3

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  1. 2023Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning
  2. 2025Single Agent Robust Deep Reinforcement Learning for Bus Fleet Control
  3. 2024RL-MSA: a Reinforcement Learning-based Multi-line bus Scheduling Approach
  4. 2024CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
  5. 2025Belief-Based Offline Reinforcement Learning for Delay-Robust Policy Optimization
  6. 2023Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration
  7. 2025DTCCL: Disengagement-Triggered Contrastive Continual Learning for Autonomous Bus Planners ↗
  8. 2024A Natural Extension To Online Algorithms For Hybrid RL With Limited Coverage