813f888502
User's insight: a circling car stays near the same track waypoints, so active_node (sim's track progress indicator) never advances. Track the maximum active_node reached this episode. If it hasn't increased in progress_patience=60 steps (~3.3s), terminate. This catches: - Circular driving (active_node oscillates, max never increases) - Stuck on cone/barrier (active_node frozen) - NOT triggered by: legitimate cornering, slow forward progress, lap resets On lap completion, active_node wraps to 0 — reset max_node_seen and counter. Also: Exp 12 — single track mountain training with lap-based stopping criterion. Train until 3 consecutive laps in eval, not fixed step count. |
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|---|---|---|
| .. | ||
| README.md | ||
| exp6_mountain_v5_proper.py | ||
| exp7_mountain_proper.py | ||
| exp8_mountain_clean.py | ||
| exp9_mountain_v5_throttle02.py | ||
| exp10_two_tracks.py | ||
| exp11_parallel_envs.py | ||
| exp11b_parallel_v6.py | ||
| exp11c_parallel_v6_250k.py | ||
| exp11d_parallel_v61.py | ||
| exp12_mountain_single.py | ||
| mountain_continue.py | ||
| mountain_high_throttle.py | ||
| mountain_v5.py | ||
| overnight.py | ||
| wave5_train.py | ||
README.md
Experiment Scripts
These scripts were used to run individual training experiments. Each corresponds to an entry in docs/TEST_HISTORY.md.
| Script | Experiment | Key change |
|---|---|---|
| mountain_v5.py | Exp 5 | v5 reward + throttle_min=0.5, direct model.learn() |
| mountain_continue.py | Exp 4 | Continued Exp3 training |
| mountain_high_throttle.py | Exp 3 | throttle_min=0.5, old v4 reward |
| exp6_mountain_v5_proper.py | Exp 6 | v5 + termination, wrong steps_per_switch (=total) |
| exp7_mountain_proper.py | Exp 7 | v5 + termination, correct steps_per_switch=6000, had phantom car issue |
| exp8_mountain_clean.py | Exp 8 | v5 + throttle_min=0.5, single connection, correct checkpointing |
| exp9_mountain_v5_throttle02.py | Exp 9 | v5 + throttle_min=0.2, OUR BEST MODEL |
| exp10_two_tracks.py | Exp 10 | Two tracks via custom script (abandoned — used multitrack_runner.py instead) |
| overnight.py | Overnight runs | mountain-only and Trial9-repeat experiments |
| wave5_train.py | Wave 5 | generated_track only with throttle_min=0.2 |
Rule going forward
ALL experiment scripts must be saved here and committed to git BEFORE running. Scripts in /tmp are lost on reboot.
Running experiments
Use multitrack_runner.py directly for two-track training: python3 multitrack_runner.py --total-timesteps 90000 --steps-per-switch 6000 ...
For single-track experiments, use the pattern from exp8/exp9:
- VecTransposeImage(DummyVecEnv([make_env])) for env creation
- Direct model.learn() loop with manual checkpointing
- No close_and_switch() for single track