Related resources
Search for item elsewhere
University researcher(s)
Academic department(s)
Theory and Practice of Optimal Mutation Rate Control in Hamming Spaces of DNA Sequences
Belavkin, R. V. Channon, A. Aston, E. Aston, J. Knight, C. G
In: Lenaerts, T; Giacobini, M; Bersini, H; Bourgine, P; Dorigo, M; Doursat, R. Advances in Artificial Life, ECAL 2011: European Conference on Artificial Life; 08 Aug 2011-12 Aug 2011; Paris. MIT; 2011. p. 85-92.
Access to files
-
FULL-TEXT.PDF (pdf)
Abstract
We investigate the problem of optimal control of mutation by asexual self-replicating organisms represented by points in a metric space. We introduce the notion of a relatively monotonic fitness landscape and consider a generalisation of Fisher’s geometric model of adaptation for such spaces. Us- ing a Hamming space as a prime example, we derive the prob- ability of adaptation as a function of reproduction parameters (e.g. mutation size or rate). Optimal control rules for the pa- rameters are derived explicitly for some relatively monotonic landscapes, and then a general information-based heuristic is introduced. We then evaluate our theoretical control func- tions against optimal mutation functions evolved from a ran- dom population of functions using a meta genetic algorithm. Our experimental results show a close match between theory and experiment. We demonstrate this result both in artifi- cial fitness landscapes, defined by a Hamming distance, and a natural landscape, where fitness is defined by a DNA-protein affinity. We discuss how a control of mutation rate could oc- cur and evolve in natural organisms. We also outline future directions of this work.