# RL-Based Alignment **Entity class:** AI-alignment method **Domain:** Artificial intelligence / Model behavior **Maturity:** Developed ## Definition RL-based alignment uses reinforcement-learning signals derived from people, models, rules, or measurable outcomes to shift a model toward preferred behavior. ## Mechanism and significance Its success depends on the reward signal and evaluation environment because a system can optimize the proxy while violating the intended objective. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#AI Control, Law, and Alignment|AI Control, Law, and Alignment]] - **Primary fields:** [[AI Control]] · [[AI Safety]] · [[AI Infrastructure Consent]] - **Adjacent concepts:** [[System Prompt]] · [[Supervised Fine-Tuning]] · [[Machine Interpretation of Intent]] · [[Three Laws of Robotics]] ## 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.