Samples car position every 100 steps during eval. Computes macro efficiency = net_displacement / total_sampled_path. If < 0.3 with >= 500 steps, logs WARNING: SHUTTLE EXPLOIT? with the efficiency value. Also logs reward/step per episode so anomalously high-scoring long episodes can be diagnosed immediately. This will tell us definitively whether Trials 9 and 14 (1435/1573 scores, 2000 steps each) were genuine driving or back-and-forth shuttling on a mini_monaco straight. Agent: pi Tests: 102 passed Tests-Added: 0 TypeScript: N/A |
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| .harness | ||
| agent | ||
| docs | ||
| tests | ||
| .gitignore | ||
| AGENT.md | ||
| DECISIONS.md | ||
| IMPLEMENTATION_PLAN.md | ||
| PROJECT-KICKOFF.md | ||
| PROJECT-SPEC.md | ||
| README.md | ||
| create_gitea_repo.py | ||
| ralph-loop.sh | ||
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