The Co-Evolution of Memetic Algorithms for Protein Structure Prediction

Abstract

This paper describes a co-evolutionary learning-optimisation approach to Protein Structure Prediction which uses a Memetic Algorithm as its underlying search method. Instance-specific knowledge can be learned, stored and applied by the system in the form of a population of rules. These rules determine the neighbourhoods used by the local search process, which is applied to each member of the co-evolving population of candidate solutions.