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donkeycar-rl-autoresearch/agent/experiments
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Paul Huliganga beb04f3ebe fix: reward v6 — efficiency gate prevents circular driving, stuck_steps 80→40 
v5 dropped the efficiency term to get gradient signal on hills, but this
re-enabled circular driving (observed in Exp 11). v6 adds efficiency back
as a GATE (not multiplier): if efficiency < 0.15, reward = 0. Otherwise
reward = speed × CTE_quality (same as v5).

Gate vs multiplier: v4 used efficiency as a multiplier which killed gradient
on hills (all terms → 0 simultaneously). v6's gate passes when efficiency
is above threshold (car moving forward, even slowly on hill) and only
blocks when car is truly circling.

Also reduced stuck_steps from 80 to 40 (~2.5s vs ~5s) — user reported
car stuck against barriers for ~10s which is too long with DummyVecEnv.
 		2026-04-19 12:02:55 -04:00
..
README.md save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp6_mountain_v5_proper.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp7_mountain_proper.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp8_mountain_clean.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp9_mountain_v5_throttle02.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp10_two_tracks.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
exp11_parallel_envs.py fix: reward v6 — efficiency gate prevents circular driving, stuck_steps 80→40 2026-04-19 12:02:55 -04:00
mountain_continue.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
mountain_high_throttle.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
mountain_v5.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
overnight.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00
wave5_train.py save: all experiment scripts moved from /tmp to agent/experiments/ 2026-04-18 21:30:08 -04:00

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