Without this, Wave 4 scratch-trained models produce no rollout stats in the log, making it impossible to monitor training progress or spot degenerate policies early. Warm-start models in Wave 3 showed stats because verbose=1 was baked into the Phase-2 saved model state; fresh models default to verbose=0. Agent: pi Tests: 96 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