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Critical mass of ideas

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  • 1. “Critical Mass of Ideas” A Model of Incubation in BrainstormingRicardo Sosa and John S Gero
  • 2. Incubation www.dilbert.comRicardo Sosa and John S Gero
  • 3. This talk www.icdc2012.org.uk Context and big picture Definitions and issues Insights Computational Social Science Modelling principles, hypotheses and results*Ricardo Sosa and John S Gero
  • 4. www.sutd.edu.sg/idc.aspxRicardo Sosa and John S Gero
  • 5. Brainstorming groups Interactive – Nominal Groups Facilitation Strategies – Unstructured Ideational Productivity – Quality Individual – Team Conditions Laboratory – Field – Computational Practice – AnalysisRicardo Sosa and John S Gero
  • 6. Incubation “A stage of creative problem solving in which a problem is temporarily put aside after a period of initial work”Ricardo Sosa and John S Gero
  • 7. Incubation Differentially advantageous: Moderators? Why and when interrupt/resume ideation? A better characterization, expected effects, appropriate conditions, best timing and management strategies Comp Soc Sci: exploratory but explicitRicardo Sosa and John S Gero
  • 8. “Critical Mass of Ideas” Ideation is significantly more productive once initial stages have produced a sufficiently large mass of base ideas Incubation amplifies and accelerates ideation A small mass is insufficient, a large mass unproductiveRicardo Sosa and John S Gero
  • 9. “Critical Mass of Ideas” CMI principle: a sufficiently rich body of initial ideas is a pre-condition for combinatory processes to generate a high number and variety of creative ideas With CMI, marginal amounts of incubation are sufficient to produce peak resultsRicardo Sosa and John S Gero
  • 10. Computational Social Model IAS: Ideas, Agents, Society (Sosa, Gero and Jennings 2009) shapeStorming –a thinking tool: A computational model of brainstorming using 2D shape emergence Design agents (A) explore, exploit and incubate solutions and design concepts (I) organised in teams (S) Experimental variables: exploration length and incubation rateRicardo Sosa and John S Gero
  • 11. Ricardo Sosa and John S Gero
  • 12. Questions and Comments Ricardo Sosa ricardo_sosa@sutd.edu.sg John S. Gero john@johngero.comRicardo Sosa and John S Gero
  • 13. Exploration – Exploitation - Incubation Explore: random arrangement of connected lines from which polygons of n-sides are built Exploit: variations to geometries guided by topological relations (design concepts) derived from previous solutions Incubate: variations to design concepts with no direct changes in geometriesRicardo Sosa and John S Gero
  • 14. Hypotheses (H1) a combination of exploration and exploitation is likely to produce a significant increase in ideational productivity (H2) incubation will produce a significant increase in ideational productivityRicardo Sosa and John S Gero
  • 15. Ricardo Sosa and John S Gero
  • 16. Emergent Shape Semantics Number of emergent polygons, number of sidesRicardo Sosa and John S Gero
  • 17. Ideation in Exploration Mode shapeStorming conditions Ideational productivity A: 1,000 steps, 4 agents, 2 initial shapes, 3 sides 7.23 B: 10,000 steps, 4 agents, 2 initial shapes, 3 sides 9.38 C: 10,000 steps, 4 agents, 3 initial shapes, 3 sides 134.22 D: 100,000 steps, 4 agents, 2 initial shapes, 3 sides 15.35Ricardo Sosa and John S Gero
  • 18. Experiment 1 Effects of exploitation mode in ideational productivity at different stages in conditions A and B Exploration length φ: from 0.0 to 1.0 in 0.05 incrementsRicardo Sosa and John S Gero
  • 19. Experiment 2 Effects of varying incubation stage against length of preparation stage in conditions A and B Incubation rate μ: from 0.0 to 0.50Ricardo Sosa and John S Gero
  • 20. Results: Exploitation Condition A: peak ideational productivity +6% with φ = 0.75 (short runs). Condition B: +93% with φ = 0.75 (long runs) In B, exploitation-driven concepts show a significant increase as exploration is extended Exploitation has positive but differentiated effects on ideational productivity depending on the ability to build on a sufficiently large mass of ideasRicardo Sosa and John S Gero
  • 21. “Critical Mass of Ideas” A significant gain in ideational productivity due to positive feedback effects between exploitation and a sufficiently large body of ideas from explorationRicardo Sosa and John S Gero
  • 22. Results: Incubation Condition A: peak ideational productivity +220% with a low incubation rate μ = 0.05 and φ = 0.20 Condition B: ideational productivity +160% when μ = 0.05 and φ = 0.10 Effects of incubation dependent on the size of the problem space addressed in ideationRicardo Sosa and John S Gero
  • 23. Discussion Incubation: put aside a problem for a time period t, once n ideas of m categories are generated CMI: used to manage interactive/nominal groupsRicardo Sosa and John S Gero
  • 24. Questions and Comments Ricardo Sosa ricardo_sosa@sutd.edu.sg John S. Gero john@johngero.comRicardo Sosa and John S Gero