donkeycar-rl-autoresearch

Commit Graph

Author	SHA1	Message	Date
Paul Huliganga	e68d618d29	feat: Phase 3 — behavioral control, enhanced evaluator, 53 tests PHASE 2 MILESTONE DOCUMENTED: All 3 top models complete the full track with distinct driving styles: - Trial 20 (n_steer=3): Right lane, stable steering — CHAMPION ✅ - Trial 8 (n_steer=4): Left/center lane, oscillating (still completes!) - Trial 18 (n_steer=3): Right shoulder, very accurate line following Key finding: fewer steering bins (n_steer=3) = better driving (counterintuitive) CTE symmetry explains left/right preference: random NN init determines which side BEHAVIORAL REWARD WRAPPERS (agent/behavioral_wrappers.py): - LanePositionWrapper: target a specific CTE offset (control left/right preference) - AntiOscillationWrapper: penalise rapid steering changes (fix Model 2 oscillation) - AsymmetricCTEWrapper: enforce right-lane rule (penalise left-of-centre more) - CombinedBehavioralWrapper: all three combined in one wrapper ENHANCED EVALUATOR (agent/evaluate_champion.py): - Full metrics: reward, lap time, oscillation score, CTE distribution, lane position - --compare flag: runs all top Phase 2 models side by side with comparison table - Saves eval summary to outerloop-results/eval_summary.jsonl - Detects lap completion events from sim info dict IMPLEMENTATION PLAN updated: Wave 3 streams defined RESEARCH LOG updated: Phase 2 milestone, behavioral analysis, next steps Champion updated to Trial 20 (Phase 2) Agent: pi/claude-sonnet Tests: 53/53 passing (+13 behavioral wrapper tests) Tests-Added: +13 TypeScript: N/A	2026-04-14 09:28:43 -04:00
Paul Huliganga	7b8830f0cb	milestone: Phase 1 complete — genuine driving confirmed; launch Phase 2 corner learning PHASE 1 MILESTONE: - Champion model drives the track for 599 steps (mean_reward=1022.78, std=0.45) - Path efficiency 96-100% throughout — genuine forward motion confirmed - Navigates first right-hand curve successfully - Fails at S-curve (right->left) at step ~560: speed too high for tight corners - Root cause: only 4787 training timesteps — model never sees S-curve enough to learn it PHASE 2 CONFIG (corner learning): - timesteps: 10,000-50,000 (10x more — model must experience S-curve many times) - learning_rate: 0.00005-0.002 (tightened around Phase 1 winning region) - eval_episodes: 5 (more reliable corner stats) - JOB_TIMEOUT: 3600s (50k steps on CPU needs time) - Results: autoresearch_results_phase2.jsonl (clean separation from Phase 1) Research documentation: - Phase 1 milestone added to docs/RESEARCH_LOG.md - Full trajectory analysis: start -> first corner -> S-curve crash position logged - Reward shaping v3 path efficiency victory documented - evaluate_champion.py added for visual + diagnostic evaluation Agent: pi/claude-sonnet Tests: 40/40 passing Tests-Added: 0 TypeScript: N/A	2026-04-13 19:33:06 -04:00

Author

SHA1

Message

Date

Paul Huliganga

e68d618d29

feat: Phase 3 — behavioral control, enhanced evaluator, 53 tests

PHASE 2 MILESTONE DOCUMENTED:
  All 3 top models complete the full track with distinct driving styles:
  - Trial 20 (n_steer=3): Right lane, stable steering — CHAMPION ✅
  - Trial 8  (n_steer=4): Left/center lane, oscillating (still completes!)
  - Trial 18 (n_steer=3): Right shoulder, very accurate line following
  Key finding: fewer steering bins (n_steer=3) = better driving (counterintuitive)
  CTE symmetry explains left/right preference: random NN init determines which side

BEHAVIORAL REWARD WRAPPERS (agent/behavioral_wrappers.py):
  - LanePositionWrapper: target a specific CTE offset (control left/right preference)
  - AntiOscillationWrapper: penalise rapid steering changes (fix Model 2 oscillation)
  - AsymmetricCTEWrapper: enforce right-lane rule (penalise left-of-centre more)
  - CombinedBehavioralWrapper: all three combined in one wrapper

ENHANCED EVALUATOR (agent/evaluate_champion.py):
  - Full metrics: reward, lap time, oscillation score, CTE distribution, lane position
  - --compare flag: runs all top Phase 2 models side by side with comparison table
  - Saves eval summary to outerloop-results/eval_summary.jsonl
  - Detects lap completion events from sim info dict

IMPLEMENTATION PLAN updated: Wave 3 streams defined
RESEARCH LOG updated: Phase 2 milestone, behavioral analysis, next steps
Champion updated to Trial 20 (Phase 2)

Agent: pi/claude-sonnet
Tests: 53/53 passing (+13 behavioral wrapper tests)
Tests-Added: +13
TypeScript: N/A

2026-04-14 09:28:43 -04:00

Paul Huliganga

7b8830f0cb

milestone: Phase 1 complete — genuine driving confirmed; launch Phase 2 corner learning

PHASE 1 MILESTONE:
- Champion model drives the track for 599 steps (mean_reward=1022.78, std=0.45)
- Path efficiency 96-100% throughout — genuine forward motion confirmed
- Navigates first right-hand curve successfully
- Fails at S-curve (right->left) at step ~560: speed too high for tight corners
- Root cause: only 4787 training timesteps — model never sees S-curve enough to learn it

PHASE 2 CONFIG (corner learning):
- timesteps: 10,000-50,000 (10x more — model must experience S-curve many times)
- learning_rate: 0.00005-0.002 (tightened around Phase 1 winning region)
- eval_episodes: 5 (more reliable corner stats)
- JOB_TIMEOUT: 3600s (50k steps on CPU needs time)
- Results: autoresearch_results_phase2.jsonl (clean separation from Phase 1)

Research documentation:
- Phase 1 milestone added to docs/RESEARCH_LOG.md
- Full trajectory analysis: start -> first corner -> S-curve crash position logged
- Reward shaping v3 path efficiency victory documented
- evaluate_champion.py added for visual + diagnostic evaluation

Agent: pi/claude-sonnet
Tests: 40/40 passing
Tests-Added: 0
TypeScript: N/A

2026-04-13 19:33:06 -04:00

2 Commits