Information AboutHuman-based Computation |
| CATEGORIES ABOUT HUMAN-BASED COMPUTATION | |
| human-based computationhuman-based computation | |
| human-computer interaction | |
| theoretical computer science | |
| technology in society | |
| collective intelligence | |
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In traditional computation, a human employs computer to solve a problem: a human provides a formalized problem description to a computer, and receives a solution to interpret. In human-based computation, the roles are reversed: computer asks a person or often a large number of people to solve a problem, then collects, interprets, and integrates their solutions. Precursors of this idea are interactive programs requesting input from a user, e.g. asking a confirmation to delete a file. However, this concept in its explicit form appeared at the intersection of computer graphics and evolutionary computation. 91 used human visual perception and esthetic ability to implement evaluation function in evolutionary programming application and evolve pieces of graphic art this way. The crucial difference here is agency: Sim's program was no longer an agent of its user, but rather a coordinator of many human evaluators who became agents of the program. Human-based genetic algorithm (HBGA) is a logical extension and a quite general model of this approach based on the idea of outsourcing. Thus, in HBGA humans also can contribute their innovative solutions into the process and have more control over the functions they are performing. Most implementations of HBGA also have some kind of motivation system that encourages humans to participate. The following table from 00 uses the evolutionary computation model to describe four classes of computation, three of which rely on humans in some role. The classification is in terms of the roles (innovation or selection) performed in each case by humans and computational processes. This table also has a third dimension, determining how agents are organized. Here we assume that organization and coordination are performed by a program.
METHODS OF HUMAN-BASED COMPUTATION
REFERENCES # 91 Sims, K.: Artificial Evolution for Computer Graphics, Computer Graphics, 25(4) (SIGGRAPH'91), 319-328 (1991) # 98 Unemi, T.: A Design of multi-field user interface for simulated breeding, Proceedings of the Third Asian Fuzzy and Intelligent System Symposium, 489-494 (1998) # 98 Alex Kosorukoff, Free Knowledge Exchange, human-based genetic algorithm on the web archive description # 98 Lillibridge et al. (1998) Method for selectively restricting access to computer systems, US Patent 6,195,698 # 99 Twenty questions: the neural-net on the Internet archive website # 00 Alex Kosorukoff (2000) Human-based genetic algorithm online # 01 Cunningham, Ward and Leuf, Bo (2001): The Wiki Way. Quick Collaboration on the Web. Addison-Wesley, ISBN 0-201-71499-X. # 01 Hideyuki Takagi (2001), Interactive Evolutionary Computation: Fusion of the Capabilities of EC Optimization and Human Evaluation, Proceedings of the IEEE, vol.89, no. 9, pp. 1275-1296 # 01 Alex Kosorukoff, Human-based Genetic Algorithm. IEEE Transactions on Systems, Man, and Cybernetics, SMC-2001, 3464-3469 # 02 Alex Kosorukoff, David E. Goldberg, Genetic algorithm as a form of organization, Proceedings of Genetic and Evolutionary Computation Conference, GECCO-2002, pp 965-972 # Ahn 03 Luis von Ahn, Manuel Blum, Nick Hopper and John Langford CAPTCHA: Using Hard AI Problems for Security In Eurocrypt 2003 # Ahn 03 Luis von Ahn Method for labeling images through a computer game US Patent Application 10/875913 # Ahn 04 Luis von Ahn and Laura Dabbish Labeling Images with a Computer Game In ACM CHI 2004 # Ahn 06 Luis von Ahn, Mihir Kedia and Manuel Blum Verbosity: A Game for Collecting Common-Sense Facts To Appear in ACM CHI Notes 2006 # Ahn 06 Luis von Ahn, Shiry Ginosar, Mihir Kedia, Rouran Liu and Manuel Blum Improving Accessibility of the Web with a Computer Game To Appear in ACM CHI Notes 2006 |
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