paulh
/
donkeycar-rl-autoresearch
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
Research-grade DonkeyCar RL autoresearch and sweep system.
42 Commits 1 Branch 0 Tags 207 MiB
Python 94.3%
Shell 5.7%
Go to file
Paul Huliganga 7534527722 Wave 4: scratch training on generated_track + mountain_track, zero-shot mini_monaco 
Strategy change driven by Trial 1 data analysis:
- generated_road removed: too similar to generated_track, and Phase-2
  warm-start caused catastrophic forgetting (reward 2388→37 in one rotation)
- mountain_track mean reward was only 17 — model never converged there
- mini_monaco score 24.9 (37 steps) — model was outputting degenerate actions

Wave 4 approach:
- NO warm-start: fresh random weights every trial
- Train: generated_track + mountain_track (visually distinct backgrounds,
  both have road markings — forces model to learn general mark-following)
- Test (zero-shot): mini_monaco only (never seen during training)
- Wider LR search: [1e-4, 2e-3] (scratch model needs different range)
- Larger step budgets: 60k-250k total (fresh model needs more time)
- Seed params: lr=0.0003 and lr=0.001 (diverse from the start)

Files:
- multitrack_runner.py: 2 training tracks, no warm-start auto-detection
- wave4_controller.py: new Wave 4 GP+UCB controller
- tests updated: TRAINING_TRACKS assertion, seed param tests → wave4
- 96 tests passing

ADR-013 to follow.

Agent: pi
Tests: 96 passed
Tests-Added: 0
TypeScript: N/A
 		2026-04-14 22:40:38 -04:00
.harness feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
agent Wave 4: scratch training on generated_track + mountain_track, zero-shot mini_monaco 2026-04-14 22:40:38 -04:00
docs wave3: add multi-track autoresearch system (83 tests passing) 2026-04-14 12:47:12 -04:00
tests Wave 4: scratch training on generated_track + mountain_track, zero-shot mini_monaco 2026-04-14 22:40:38 -04:00
.gitignore feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
AGENT.md feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
DECISIONS.md wave3: add multi-track autoresearch system (83 tests passing) 2026-04-14 12:47:12 -04:00
IMPLEMENTATION_PLAN.md feat: Phase 3 — behavioral control, enhanced evaluator, 53 tests 2026-04-14 09:28:43 -04:00
PROJECT-KICKOFF.md feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
PROJECT-SPEC.md feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
README.md feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00
create_gitea_repo.py Initial commit 2026-04-12 23:44:36 -04:00
ralph-loop.sh feat: Wave 1 complete — real PPO training, model save, GP+UCB autoresearch, 37 tests passing 2026-04-13 10:03:15 -04:00

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