Publications


MixItUp Demo - Toggle Filtering AND Logic



Exploiting the relationship between structural modularity and sparsity for faster network evolution

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, , 1173-1176, 2015


Status: Published

Citations:

Cite: [bibtex]


My Image

Abstract: A network is structurally modular if it can be divided into tightly connected groups which are weakly connected or disconnected from each other. Such networks are known to be capable of fast evolutionary adaptation, which makes modularity a highly desired property of networks involved in evolutionary computation. Modularity is known to correlate positively with another network parameter, sparsity. Based on this relationship, we hypothesize that starting evolution with a population of sparse networks should increase the modularity of the evolved networks. We find that this technique can enhance the performance of an existing technique for modularity evolution, multiobjective performance-connection cost (P&CC) optimization, and enable a multiobjective algorithm which maximizes performance and minimizes time since last mutation to produce modular solutions almost as efficiently as the P&CC optimization does.



[edit database entry]
Stacks Image 525289
(null)

  • Stacks Image 525371
    (null)
  • Stacks Image 525379
    (null)
  • Stacks Image 525375
    (null)


Stacks Image 525306
(null)

  • Stacks Image 525319
    (null)
  • Stacks Image 525314
    (null)
  • Stacks Image 525310
    (null)


Stacks Image 525327
(null)

  • Stacks Image 525331
    (null)
  • Stacks Image 525335
    (null)
  • Stacks Image 525339
    (null)


Stacks Image 525346
(null)

  • Stacks Image 525350
    (null)
  • Stacks Image 525354
    (null)
  • Stacks Image 525358
    (null)


Stacks Image 525386
(null)

  • Stacks Image 525390
    (null)
  • Stacks Image 525394
    (null)
  • Stacks Image 525398
    (null)