Tycho: Active Abstraction with Programmatic World Models for ARC-AGI-3

TL;DR - Tycho is a coding-agent system that builds and selectively uses executable world models to solve interactive ARC-AGI-3 games efficiently. Its results suggest that deciding when to construct, repair, use, or bypass a model is as important as simulator accuracy.

• Tycho models games as parameterized rendered deterministic Moore machines and separates actionable states from animation and terminal frames.
• Actor-requested delegation to a model builder achieved the best tested orchestration result, averaging 88.49 Relative Human Action Efficiency across 25 public games.
• With that policy, GPT-5.6 Sol and Opus 5 completed all 183 levels at 100.00 RHAE; Opus 5 used 61% fewer scored actions than aggregate official human baselines.
• Automatic model repair improved transition reproduction but reached only 83.07 RHAE, showing that dynamics accuracy alone does not ensure effective planning or objective discovery.