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Phase 4 adds the Semantics and Causal Inference Engine: semantic signatures, causal transition models, hypothesis confirm/refute, counterfactual queries, and epistemic uncertainty over (state, action) pairs—building on Phases 1–3. The article presents theory and architecture; a companion Kaggle notebook deploys CausalSemanticsEngine hints for ARC Prize 2026.
Phase 3 extends ASRA with the Navigation and Memory Engine: exploration graphs, visitation memory, novelty versus usefulness scoring, compositional subgoals, strategy reuse, and transition replay—building on Phase 1 transitions and Phase 2 object-centric observation. The article presents theory and architecture; a companion Kaggle notebook deploys compact exploration hints for ARC Prize 2026.
Phase 1 established interactive intelligence from transition evidence alone; Phase 2 adds the Observation Engine—segmentation, object alignment, transform events, and rule candidates over ARC demonstration pairs, with compact object-scene hints feeding back into the interactive agent. This article presents the theory, architecture, and design principles for object-centric structure between Phase 1 logging and later memory, causality, and planning.
Phase 1 establishes the ASRA Experience Engine: transition logging, hash-stable state IDs, effect-based action semantics inference, uncertainty-directed exploration, dead-end taboo, Swarm orchestration, and competition-grade execution fidelity. The article presents full theory and architecture; a companion Kaggle notebook deploys asra-v0.1-phase1 for ARC Prize 2026.