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donkeycar-rl-autoresearch
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Research-grade DonkeyCar RL autoresearch and sweep system.
71 Commits 1 Branch 0 Tags 207 MiB
Python 94.3%
Shell 5.7%
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Paul Huliganga fecba1dd35 docs: TEST_HISTORY Exp10 plan added 
Exp10: generated_track + mountain_track, v5 reward, throttle_min=0.2
Same as Exp9 but with visual diversity from second track.

Agent: pi
 		2026-04-18 17:59:07 -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 feat: run_eval.py — standard eval runner with persistent logging 2026-04-18 15:32:36 -04:00
docs docs: TEST_HISTORY Exp10 plan added 2026-04-18 17:59:07 -04:00
tests fix: short-lap exploit now TERMINATES the episode, not just penalises 2026-04-18 10:42:23 -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 docs: ADR-017 — always save best model, never just latest 2026-04-17 16:03:59 -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