A computational view of population genetics

This paper contributes tothe study of nonlinear dynamical systems from a computational perspective. These systems are inherently more powerful than their linear counterparts (such as Markov chains), which have had a wide impact in Computer Science, and they seem likely to play an increasing role in future. However, there are as yet no general techniques available for handling the computational aspects of discrete nonlinear systems, and even the simplest examples seemvery hard to analyze. We focus in this paper on a class of quadratic systems that are widely used as a model in population genetics and also in genetic algorithms. These systems describe a process where random matingsoccur between parental chromosomes via a mechanism known as \crossover": i.e., children inherit pieces of genetic material from di erent parents according to some random rule. Our results concern two fundamental quantitative properties of crossover systems:

• Type: Conference
• Year: 1995
• Where: STOC
• Authors: Yuval Rabani, Yuri Rabinovich, Alistair Sinclair
• Keywords: Algorithms, Children Inherit Pieces, Discrete Nonlinear Systems, Nonlinear Dynamical Systems, STOC 1995