The short-lap episode termination fix in SpeedRewardWrapper was not working when multitrack_runner.py ran via command line because the env was created as a plain gym.Wrapper chain, not VecTransposeImage(DummyVecEnv). In custom scripts (Exp8, Exp9), env was explicitly: VecTransposeImage(DummyVecEnv([make_env])) This made episode termination work correctly. In multitrack_runner.py, env was just wrap_env(raw) — a plain gym.Wrapper. SB3 auto-wraps this internally but the terminated signal from SpeedRewardWrapper.force_terminate did not propagate correctly, so circle-exploit episodes were never terminated during training. Fix: use VecTransposeImage(DummyVecEnv([...])) explicitly in main(). Agent: pi Tests: 102 passed Tests-Added: 0 TypeScript: N/A |
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| .harness | ||
| agent | ||
| docs | ||
| tests | ||
| .gitignore | ||
| AGENT.md | ||
| DECISIONS.md | ||
| IMPLEMENTATION_PLAN.md | ||
| PROJECT-KICKOFF.md | ||
| PROJECT-SPEC.md | ||
| README.md | ||
| create_gitea_repo.py | ||
| ralph-loop.sh | ||
README.md
donkeycar-rl-autoresearch
Purpose
Status
- Scaffolded with the agent harness
- Spec not filled yet
Runbook
- Fill PROJECT-SPEC.md
- Create IMPLEMENTATION_PLAN.md from the spec
- Start the implementation loop