# Latent Behavioral Algorithm **Entity class:** Computational-behavior concept **Domain:** Cognitive science / Animal behavior **Maturity:** Developed ## Definition A latent behavioral algorithm is an inferred internal rule or computation that explains how an organism converts perception, state, and memory into action. ## Mechanism and significance The algorithm is not directly observed; it earns credibility by predicting behavior across conditions and surviving experimental intervention. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#Neural Decoding and Cognitive Systems|Neural Decoding and Cognitive Systems]] - **Primary fields:** [[Neural Decoding]] · [[Brain-Computer Interfaces]] · [[Functional Magnetic Resonance Imaging]] - **Adjacent concepts:** [[Biological Neural Dynamics]] · [[Sam Gershman]] ## Sources and provenance - [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] — immediate source for this node's role in the broadcast research map. ## Evidence boundary The research dossier establishes why this entity or concept belongs in the Moonshots ontology. Time-sensitive organizational, product, policy, and performance claims should be checked against the linked primary source or a current authoritative source before reuse as settled fact.