Many congrats Dr. Albert Orriols-Puig

On Friday 12, Albert Orriols received his PhD degree. He presented his work entitled New challenges in learning classifier systems: Mining rarities and evolving fuzzy models with a magnificent mise-en-scène which deserved the most sincere congratulations of the examining committee, especially from Prof. Goldberg who remarked that it was one of the best dissertation […]

On Friday 12, Albert Orriols received his PhD degree. He presented his work entitled New challenges in learning classifier systems: Mining rarities and evolving fuzzy models with a magnificent mise-en-scène which deserved the most sincere congratulations of the examining committee, especially from Prof. Goldberg who remarked that it was one of the best dissertation […]

A little participation at ICPR 2008

The International Conference on Pattern Recognition finished last Thursday in Tampa, Florida. 1631 papers by 3556 authors from 47 countries were submitted of which 1006 were accepted and grouped into 74 regular and 16 poster sessions. In one of the latter, we found a work on synthetic data set generation based on […]

The International Conference on Pattern Recognition finished last Thursday in Tampa, Florida. 1631 papers by 3556 authors from 47 countries were submitted of which 1006 were accepted and grouped into 74 regular and 16 poster sessions. In one of the latter, we found a work on synthetic data set generation based on […]

Incorporating characteristics of human creativity into an evolutionary art algorithm

Abstract  A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects
the most aesthetically pleasing variants of one generation to produce the next. This paper discusses how c…

Abstract  A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects
the most aesthetically pleasing variants of one generation to produce the next. This paper discusses how computer generated
art and design can become more creatively human-like with respect to both process and outcome. As an example of a step in
this direction, we present an algorithm that overcomes the above limitation by employing an automatic fitness function. The
goal is to evolve abstract portraits of Darwin, using our 2nd generation fitness function which rewards genomes that not just
produce a likeness of Darwin but exhibit certain strategies characteristic of human artists. We note that in human creativity,
change is less choosing amongst randomly generated variants and more capitalizing on the associative structure of a conceptual
network to hone in on a vision. We discuss how to achieve this fluidity algorithmically.

  • Content Type Journal Article
  • Category Original Paper
  • DOI 10.1007/s10710-008-9074-x
  • Authors
    • Steve DiPaola, Simon Fraser University Surrey BC Canada
    • Liane Gabora, University of British Columbia Kelowna BC Canada