Abstract
This chapter discusses a computational model for collective problem solving that enables distributed individuals to describe a complex problem and to explore possible solutions. In this case, crowdsourcing is applied to the whole process of problem solving. Contributors will be involved in defining and decomposing problems in addition to finding and evaluating potential solutions. The goal of this chapter is to introduce tools for a particular kind of collective action—one in which contributors collaborate to solve problems in which they have a personal interest or stake.
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Notes
- 1.
Example of Means-Ends Analysis, Rutgers University. http://www-rci.rutgers.edu/ cfs/472_html/Planning/GPS_472.html
- 2.
Based on a semantic network at http://en.wikipedia.org/wiki/Semantic_network, accessed 3/10/13.
References
Arrow KJ (1950) A difficulty in the concept of social welfare. J Polit Econ 58:328–346. http://econpapers.repec.org/RePEc:ucp:jpolec:v:58:y:1950:p:328
Dechter R (1992) Constraint networks. In: Encyclopedia of articial intelligence, 2nd edn. Wiley, pp. 276–285
Fatima A (2011) How has the root cause analysis evolved since inception? Bright Hub PM. Http://www.brighthubpm.com/risk-management/123244-how-has-the-root-cause-analysis-evolved-since-inception/
Gravetter F, Wallnau L (2012) Statistics for the behavioral sciences, 9th edn. Cengage Learning, Andover
Greene K, Kniss J, Luger G (2010) Representing diversity in communities of bayesian decision-makers. In: Proceedings of the IEEE international conference on social computing, social intelligence and networking symposium, Minneapolis
Kindermann R, Snell JL (1980) Markov random fields and their applications. American Mathematical Society, Providence
Miller R (1981) Simultaneous statistical inference. Springer, New York
Newell A, Simon H (1963) GPS: a program that simulates human thought. In: Feigenbaum EA, Feldman J (eds) Computers and thought. McGraw-Hill, New York
Rooney J, Heuvel LV (2004) Root cause analysis for beginners. Qual Prog 37(7):45
Shachter RD (1986) Evaluating influence diagrams. Oper Res 34(6):871–882. doi:http://dx.doi.org/10.1287/opre.34.6.871
Sowa J (1992) Semantic networks. In: Shapiro SC (ed) Encyclopedia of artificial intelligence. Wiley, New York
Acknowledgements
Without the thoughtful contributions from Thomas Young, Pietro Michelucci, George Luger, Joe Kniss, Melanie Moses, and Steven Garcia, this work would not have been possible.
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Greene, K.A., Young, T.A. (2013). Building Blocks for Collective Problem Solving. In: Michelucci, P. (eds) Handbook of Human Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8806-4_28
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DOI: https://doi.org/10.1007/978-1-4614-8806-4_28
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