CounterPlay: Counterfactual Post-Training for Self-Play Driving Policies
cs.RO
Submitted: 2026-09-18
Updated: 2026-09-18
Code: https://github.com/Emerge-Lab/PufferDrive
Terminology
Sources
- Building reliable sim driving agents by scaling self-play
- Post-Training in End-to-End Autonomous Driving
- CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policies
- Beyond Self-Play and Scale: A Behavior Benchmark for Generalization in Autonomous Driving
- CoPark: Learning Reactive Parking via Self-Play
- What Emerges and What Breaks in Self-Play Driving
- Human-like autonomy emerges from self-play and a pinch of human data
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving
- World Models as Adversaries: Multi-Agent Self-Play Fine-Tuning for Robust Motion Planning
- Backplay: "Man muss immer umkehren"
- Reward-Conditioned Policies
- Proximal Policy Optimization Algorithms
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