Speeding online synthesis via enforced selecto-recombination

Brainstorming has been greatly used as a method to generate a large number of ideas by variety of each participant's knowledge. However, brainstorming does not always work well because of spatial and communication limitations. Moreover, brainstorming techniques present limited scalability. Meanwhile, genetics algorithms have been mostly regarded as an engineering or technological tool. However, the innovation intuition suggests that genetic algorithms may be also regarded as models of human innovation and creativity. This paper focuses on online creativity sessions. Modeling those creative efforts using selecto-recombinative mechanism can provide three times more novel ideas, increase the posting frequency by a 2.6 factor, and help overcome superficiality on online communications by favoring synthetic thinking.

[1]  Knut Holt.  Brainstorming—From Classics to Electronics , 1996 .

[2]  Jay F. Nunamaker,et al.  ELECTRONIC BRAINSTORMING AND GROUP SIZE , 1992 .

[3]  Xavier Llorà,et al.  Towards billion-bit optimization via a parallel estimation of distribution algorithm , 2007, GECCO '07.

[4]  Robert O. Briggs,et al.  Causal Relationships in Creative Problem Solving: Comparing Facilitation Interventions for Ideation , 2004, J. Manag. Inf. Syst..

[5]  Giacomo Mauro DAriano.  The Journal of Personality and Social Psychology. , 2002 .

[6]  Jay F. Nunamaker,et al.  An Examination of the Impact of Stimuli Type and GSS Structure on Creativity: Brainstorming Versus Non-Brainstorming Techniques in a GSS Environment , 2002, J. Manag. Inf. Syst..

[7]  Hideyuki Takagi,et al.  Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation , 2001, Proc. IEEE.

[8]  David E. Goldberg,et al.  The Design of Innovation: Lessons from and for Competent Genetic Algorithms , 2002 .

[9]  Michael Diehl,et al.  Productivity loss in idea-generating groups: Tracking down the blocking effect. , 1991 .

[10]  Terence C. Fogarty.  Automatic Concept Evolution (ACE) , 2005 .

[11]  Xavier Llorà,et al.  INNOVATION AND CREATIVITY SUPPORT VIA CHANCE DISCOVERY, GENETIC ALGORITHMS, AND DATA MINING , 2006 .

[12]  M. Diehl,et al.  Productivity loss in brainstorming groups: Toward the solution of a riddle. , 1987 .

[13]  David E. Goldberg,et al.  Discovering Building Blocks for Human Based Genetic Algorithms , 2007 .

[14]  Alex Kosorukoff,et al.  Human based genetic algorithm , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[15]  David E. Goldberg,et al.  Evolutionary Computation As A Form Of Organization , 2002, GECCO.

[16]  A. Osborn.  Applied Imagination: Principles and Procedures of Creative Thinking , 1953 .

[17]  Xavier Llorà,et al.  Delineating Topic and Discussant Transitions in Online Collaborative Environments , 2007, ICEIS.

[18]  D. Goldberg,et al.  Teamwork For A Quality Education: Low Cost, E Ective Educational Reform Through A Department Wide Competition Of Teams , 1998 .

[19]  Xavier Llorà,et al.  Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness , 2005, GECCO '05.