# Optimization > **Machine-Evolution Nexus:** [[articles/Digital Darwinism and the Invisible World of Machine Evolution|Digital Darwinism and the Invisible World of Machine Evolution]] places this concept within the history and governance of substrate-independent evolution. **Domain:** Computation / Search **Doc Type:** Canonical Wiki Node **Maturity:** Developed ## Definition Optimization is the search for states or parameters that improve an objective under constraints. ## Machine-Evolution Context Gradient methods, search algorithms and selection can all optimize, but their causal mechanisms differ. A fixed-target optimizer need not reproduce or form an evolving population. ## Continuity and Evidence Boundary An objective function encodes governance; good performance against it does not establish legitimacy, welfare or alignment outside the measured environment. ## Relationships [[wiki/Objective Function|Objective Function]], [[wiki/Genetic Algorithm|Genetic Algorithm]], [[wiki/Evolutionary Computation|Evolutionary Computation]], [[wiki/AI Governance|AI Governance]] ## Sources / Provenance - Boyd and Vandenberghe, _Convex Optimization_; evolutionary-computation literature.