38 lines
1.7 KiB
Markdown
38 lines
1.7 KiB
Markdown
# Execution Master — DonkeyCar RL Autoresearch
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## Wave Status
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| Wave | Description | Status |
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|------|-------------|--------|
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| Wave 1 | Real Training Foundation | 🟠 In progress |
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| Wave 2 | Multi-Track Generalization | ⏸️ Not started |
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| Wave 3 | Racing / Speed Optimization | ⏸️ Not started |
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## Active Streams
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| Stream | Branch | Status | Blocker |
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|--------|--------|--------|---------|
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| 1A: Core Runner Rebuild | main | 🟠 In progress | None |
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| 1B: Tests | main | ⏸️ Planned | 1A-01 must complete first |
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| 1C: First Real Autoresearch | main | ⏸️ Planned | 1A + 1B complete, sim running |
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## Wave 1 Gate Criteria
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Before starting Wave 2, ALL must be true:
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- [ ] All 1A, 1B, 1C tasks checked off in IMPLEMENTATION_PLAN.md
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- [ ] `pytest tests/ -v` — all tests green
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- [ ] Champion model exists at `agent/models/champion/model.zip`
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- [ ] Champion mean_reward > 100 on training track
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- [ ] `champion_manifest.json` exists and is valid
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- [ ] Regression baseline saved
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- [ ] Wave 1 process eval written: `.harness/wave1/process-eval.md`
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- [ ] All results pushed to Gitea
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## Parallelism Rules
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1. 1A and 1B can run in parallel (1B mocks the env)
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2. 1C cannot start until 1A AND 1B are complete
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3. Wave 2 cannot start until Wave 1 gate passes
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4. Only one stream touches the sim at a time (1C has exclusive sim access)
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## Current Agent Context
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- **Active task:** 1A-01 — Rebuild donkeycar_sb3_runner.py with real PPO training
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- **Read:** PROJECT-SPEC.md, DECISIONS.md, then pick from IMPLEMENTATION_PLAN.md
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- **Important:** The existing autoresearch_results.jsonl contains RANDOM POLICY data — do not mix with Phase 1 real training results. New results go to `autoresearch_results_phase1.jsonl`
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