Quantitative Logics for Directed Evolution of an Asexual Population

Directed evolution of asexual populations is expected to offer a wide range of benefits to humanity. Achieving efficient directed evolution (DE) requires a quantitative formulation of the experimental methodologies—or logics—that can address potential challenges throughout the evolutionary process. In this article, I introduce ten logics designed for specific purposes in DE, accompanied by their mathematical formulations. To illustrate their application, I consider a hypothetical scenario of evolving an imaginary asexual population limb into a wing, employing a matrix-based discretization method to represent the trait of interest. The results indicate that applying these logics can accelerate the evolutionary process by roughly tenfold, while achieving an average accuracy of approximately 85% in reaching the desired trait across ten simulation iterations. Based on these findings, I discuss key considerations for implementing quantitative logic–based DE, propose strategies to improve alignment between the final outcome and the target trait, and examine factors for making the discretization method practical. Finally, I explore potential connections between quantitatively guided DE processes and emerging technologies, such as artificial intelligence and quantum computation.