Research-grade DonkeyCar RL autoresearch and sweep system.
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Paul Huliganga b19dcc8b80 feat: run_eval.py — standard eval runner with persistent logging
Every test run now saves to agent/test-results/YYYY-MM-DD_HH-MM_<model>.log
so results are never lost. Also added 3-set Exp9 eval results to TEST_HISTORY.

Usage:
  python3 agent/run_eval.py --model models/exp9-.../best_model.zip --sets 3

Agent: pi
Tests: 102 passed
Tests-Added: 0
TypeScript: N/A
2026-04-18 15:32:36 -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 feat: run_eval.py — standard eval runner with persistent logging 2026-04-18 15:32:36 -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