Research map / Reinforcement learning / Offline RL
Offline Reinforcement Learning with Implicit Q-Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use IQL instead of CQL | Offline RL · Ant Maze D4RL tasks | normalized score: 303.6 -> 378.0 | Helped |
| Use IQL instead of CQL | Offline RL · MuJoCo locomotion D4RL tasks | normalized score: 698.5 -> 692.4 | No clear effect |
| Use a larger expectile parameter τ (ablation) | IQL · Ant Maze tasks requiring trajectory stitching | normalized score | Helped |
| Use a larger expectile parameter τ (ablation) | IQL · Ant Maze tasks | normalized score | Helped |
Closest papers by meaning
- A Perspective of Q-value Estimation on Offline-to-Online Reinforcement Learning (AAAI 2024 · similarity 0.93)
- Exclusively Penalized Q-learning for Offline Reinforcement Learning (NeurIPS 2024 · similarity 0.92)
- Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning (ICLR 2025 · similarity 0.92)
- Towards Robust Offline Reinforcement Learning under Diverse Data Corruption (ICLR 2024 · similarity 0.91)
- C2IQL: Constraint-Conditioned Implicit Q-learning for Safe Offline Reinforcement Learning (ICML 2025 · similarity 0.91)
- On the Complexity of Offline Reinforcement Learning with Q*-Approximation and Partial Coverage (NeurIPS 2026 · similarity 0.91)
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