Topologically Inspired Walks on Randomly Connected Landscapes With Correlated Fitness

Frontiers in Physics

Grewal, Rajdeep Kaur¹  Sinha, Saptarshi¹  Roy, Soumen¹ 

[1] Department of Physics, Bose Institute, India

关键词: Fitness landscapes;    Network Science;    random networks;    Non-adaptive evolution;    Epistasis;   

DOI  :  10.3389/fphy.2018.00138

学科分类：物理（综合）

来源: Frontiers

【 摘 要 】

Strictly adaptive walks on uncorrelated and correlated fitness landscapes have been a subject of intense research. However, some experimental findings tend to advance the notion of non-adaptive evolution in terms of epistasis. To address such evolutionary paths, herein we introduce the concept of topologically inspired walks on connected and correlated landscapes with complex topologies. These walks are dictated solely by the topology of connections and are not explicitly dependent on the underlying fitness values. In the biologically significant regime of sparse randomness, we observe that such topologically inspired walks might carry a population to a local optimum even faster than strictly adaptive walks. This effect becomes more pronounced with increasing correlations in fitness. We observe interesting tradeoffs between topologically inspired walks governed by the minimum and maximum value of a set of given network metrics.

【 授权许可】

CC BY