Speeding online synthesis via enforced selecto-recombination

ABSTRACT

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.

REFERENCES

• 1: M. Diehl and W. Stroebe. Productivity loss in brainstorming groups: Toward the solution of a riddle. Journal of Personality and Social Psychology, 53(3):497--509, 1987.
• 2: M. Diehl and W. Stroebe. Productivity loss in idea-generating groups: Tracking down the blocking effect. Journal of personality and social psychology, 61(3):392--403, 1991.
• 3: T. C. Fogarty. Automatic concept evolution (ACE). In Proceedings of Genetic and Evolutionary Computation Conference 2005 (GECCO'05), Washington D. C., June 2005. Late Breaking Paper.
• 4: R. B. Gallupe, A. R. Dennis,W. H. Cooper, J. S. Valacich, L. M. Bastianutti, and J. F. N. Jr. Electronic brainstorming and group size. The Academy of Management Journal, 35(2):350--369, 1992.
• 5: D. E. Goldberg. Computer-aided gas pipeline operation using genetic algorithms and rule learning. PhD thesis, University of Michigan. Ann Arbor, MI, 1983.
• 6: David E. Goldberg, The Design of Innovation: Lessons from and for Competent Genetic Algorithms, Kluwer Academic Publishers, Norwell, MA, 2002
• 7: D. E. Goldberg, W. B. Hall, L. Krussow, E. Lee, and A. Walker. Teamwork for a quality education: low-cost, effective educational reform, through a department-wide competition of teams. Technical Report 98005, IlliGAL, 1998.
• 8: D. E. Goldberg, M. Welge, and X. Llorà. Discus: Distributed Innovation and Scalable Collaboration In Uncertain Settings. Technical Report 2003017, IlliGAL, June 2003.
• 9: Jillian M. Hender , Douglas L. Dean , Thomas L. Rodgers , Jay F. Nunamaker, Jr., An Examination of the Impact of Stimuli Type and GSS Structure on Creativity: Brainstorming Versus Non-Brainstorming Techniques in a GSS Environment, Journal of Management Information Systems, v.18 n.4, p.59-85, Number 4/Spring 2002
• 10: K. Holt. Brainstorming-from classics to electronics. Engineering Design, 7(1):77--82, 1996.
• 11: A. Kosorukoff. Human based genetic algorithm. Technical Report 2001004, IlliGAL, 2001.
• 12: Alexander Kosorukoff , David E. Goldberg, Evolutionary Computation As A Form Of Organization, Proceedings of the Genetic and Evolutionary Computation Conference, p.965-972, July 09-13, 2002
• 13: X. Llorà, D. E. Goldberg, Y. Ohsawa, N. Matsumura, Y. Washida, H. Tamura, M. Yoshikawa, M. Welge, L. Auvil, D. Searsmith, K. Ohnishi, and C.-J. Chao. Innovation and Creativity Support via Chance Discovery, Genetic Algorithms, and Data Mining. Journal of New Mathematics and Natural Computation, 2(1):85--100, 2006.
• 14: Xavier Llorà , Kumara Sastry , David E. Goldberg , Abhimanyu Gupta , Lalitha Lakshmi, Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness, Proceedings of the 2005 conference on Genetic and evolutionary computation, June 25-29, 2005, Washington DC, USA [doi>10.1145/1068009.1068228]
• 15: A. F. Osborn. Applied Imagination: Principles and Procedures of Creative Thinking. Charles Scribner's Sons, 1957.
• 16: Eric L. Santanen , Robert O. Briggs , Gert-Jan De Vreede, Causal Relationships in Creative Problem Solving: Comparing Facilitation Interventions for Ideation, Journal of Management Information Systems, v.20 n.4, p.167-198, Number 4/Spring 2004
• 17: Kumara Sastry , David E. Goldberg , Xavier Llora, Towards billion-bit optimization via a parallel estimation of distribution algorithm, Proceedings of the 9th annual conference on Genetic and evolutionary computation, July 07-11, 2007, London, England [doi>10.1145/1276958.1277077]
• 18: H. Takagi. Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation. In Proceedings of the IEEE, volume 89, pages 1275--1296, September 2001.
• 19: T. Ueda, N. I. Yasui, X. Llorà, K. Sastry, and D. Goldberg. Discovering building blocks for human based genetic algorithms. In Proceedings of Artificial Neural Networks in Engineering 2007 (ANNIE'07), Saint Louis, Missouri, November 2007.
• 20: N. I. Yasui, X. Llorà, D. E. Goldberg, Y. Washida, and H. Tamura. Delineating topic and discussant transitions in online collaborative environments. In Proceedings of 9th International Conference on Enterprise Information Systems (ICEIS'07), pages 14--21, Funchal, Portugal, June 2007.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.3 Communications Applications

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces

General Terms:
Algorithms, Design, Experimentation

Keywords:
brainstorming, creativity, human-based genetic algorithms, innovation, online discussion, superficiality on online communication