|Abstract:||This paper explores the connection between OT models of natural language and the class of computational models known as Genetic Algorithms. Genetic algorithms have been used to model the acquisition of syntax cast in a Principles and Parameters (P&P) framework. Unlike the P&P work, where the genetic algorithm is added to the theory as the acquisition component, I make the strong claim that an OT system properly construed *is* a genetic algorithm. To the extent that genetic algorithms are an adequate model of acquisition, this entails that one OT system can acquire another. I briefly describe a model of language acquisition where an OT system is used to acquire the constraint rankings of other OT systems. The model crucially depends on both serial and parallel operation, suggesting that both modes have a role in the formulation of OT. In addition, the model provides a relatively detailed description of Gen which is consistent with the assumptions of OT.