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donkeycar-rl-autoresearch/agent/experiments
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Paul Huliganga b504b89b2a feat: add exp17 parallel DummyVecEnv 450k training + strategy docs 
- exp17_parallel_450k.py: parallel two-track training (generated_track:9091,
  mountain_track:9093), 450k steps, v6 reward, HOST=localhost
- DECISIONS.md: ADR-025 (parallel strategy) and ADR-026 (mountain friction fix)
- docs/STATE.md: updated to April 2026 state with current champions and strategy
- docs/TEST_HISTORY.md: mountain friction fix notes + Exp 17 full design
- outerloop-results: exp14 finetune logs and robust mountain eval results

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 		2026-04-28 02:42:20 -04:00
..
README.md feat: add exp17 parallel DummyVecEnv 450k training + strategy docs 2026-04-28 02:42:20 -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
exp11b_parallel_v6.py feat: Exp 11b — parallel DummyVecEnv + v6 reward (anti-circle gate) + built-in eval 2026-04-19 12:03:46 -04:00
exp11c_parallel_v6_250k.py feat: Exp 11c — parallel DummyVecEnv + v6 reward, extended to 250k steps 2026-04-19 13:27:38 -04:00
exp11d_parallel_v61.py fix: exp11d remove progress_patience — grass fix only per ADR-020 2026-04-19 16:18:17 -04:00
exp12_mountain_single.py fix: reward v6.1 — active_node progress terminator kills circle/stuck exploits 2026-04-19 17:01:41 -04:00
exp13_gentrack_v4.py feat: Exp 13 — generated_track, v4 reward, back to basics (no extra heuristics) 2026-04-19 17:33:17 -04:00
exp14_finetune_v5.py fix: import json, use make_env_base in phase switch, and run eval sequentially to avoid second concurrent sim car 2026-04-19 20:37:25 -04:00
exp14_mountain_v5.py fix: exp14 — proper track switch via exit_scene before connecting to mountain_track 2026-04-19 19:18:33 -04:00
exp15_gentrack_from_mountain.py fix: force scene reset before exp15 generated-track warm-start so sim actually loads generated_track 2026-04-20 16:36:00 -04:00
exp16_mountain_from_gentrack.py feat: add cross-track warm-start experiments for mountain->generated and generated->mountain 2026-04-20 16:34:24 -04:00
exp17_parallel_450k.py feat: add exp17 parallel DummyVecEnv 450k training + strategy docs 2026-04-28 02:42:20 -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
exp17_parallel_450k.py Exp 17 Parallel DummyVecEnv, 450k steps, v6 reward, HOST=localhost
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