How the Obscure Features Hypothesis Leads to Innovation Assistant Software: Unterschied zwischen den Versionen
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== Abstract == | == Abstract == | ||
| + | A new cognitive theory of innovation, the Obscure | ||
| + | Features Hypothesis (OFH), states that almost all inno- | ||
| + | vative solutions result from two steps: (1) noticing a | ||
| + | rarely noticed or never-before noticed (i.e., obscure) | ||
| + | feature of the problem’s elements, and (2) building a | ||
| + | solution based on that obscure feature (McCaffrey | ||
| + | 2011). Structural properties of the human semantic | ||
| + | network make it possible to locate useful obscure fea- | ||
| + | tures with a high probability. Innovation Assistant (IA) | ||
| + | software interactively guides human users to the most | ||
| + | likely obscure features for solving the problem at hand. | ||
== Extended Abstract == | == Extended Abstract == | ||
| Zeile 13: | Zeile 24: | ||
== Used References == | == Used References == | ||
| + | Chrysikou, E. (2006). When shoes become hammers: | ||
| + | Goal-derived categorization training enhances problem- | ||
| + | solving performance. Journal of Experimental Psychology: | ||
| + | Learning, Memory, and Cognition, 32(4), 935-942. | ||
| + | |||
| + | Koza, J.R. (1994). Genetic Programming II: Automatic | ||
| + | Discovery of Reusable Programs, MIT Press. | ||
| + | |||
| + | McCaffrey, A. J. (2011). The obscure features hypothesis | ||
| + | for innovation: One key to improving human innovation. | ||
| + | Unpublished doctoral dissertation, University of Massa- | ||
| + | chusetts Amherst. | ||
| + | |||
| + | Miller, G. A. (1995). WordNet: A lexical database for Eng- | ||
| + | lish. Communications of the ACM, 38(11), 39-41. | ||
| + | |||
| + | Murphy, G. L., & Medin, D. L. (1985). The role of theories | ||
| + | in conceptual coherence. Psychological Review, 92, 289- | ||
| + | 316. | ||
| + | |||
| + | Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1998). | ||
| + | The University of South Florida word association, rhyme, | ||
| + | and word fragment norms. | ||
| + | |||
| + | Spector, L. (2008). Introduction to the special issue on | ||
| + | Genetic Programming for human-competitive designs. In | ||
| + | AI-EDAM: Artificial Intelligence for Engineering Design, | ||
| + | Analysis and Manufacturing, 22(3), 183-184. | ||
| + | |||
| + | Watts, D. J. (1999). Small worlds: The dynamics of net- | ||
| + | works between order and randomness, Princeton Univer- | ||
| + | sity Press. | ||
Version vom 30. Januar 2015, 20:57 Uhr
Inhaltsverzeichnis
Reference
Tony McCaffrey and Lee Spector: How the Obscure Features Hypothesis Leads to Innovation Assistant Software. In: Computational Creativity 2011 ICCC 2011, pp. 120-122.
DOI
Abstract
A new cognitive theory of innovation, the Obscure Features Hypothesis (OFH), states that almost all inno- vative solutions result from two steps: (1) noticing a rarely noticed or never-before noticed (i.e., obscure) feature of the problem’s elements, and (2) building a solution based on that obscure feature (McCaffrey 2011). Structural properties of the human semantic network make it possible to locate useful obscure fea- tures with a high probability. Innovation Assistant (IA) software interactively guides human users to the most likely obscure features for solving the problem at hand.
Extended Abstract
Bibtex
Used References
Chrysikou, E. (2006). When shoes become hammers: Goal-derived categorization training enhances problem- solving performance. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(4), 935-942.
Koza, J.R. (1994). Genetic Programming II: Automatic Discovery of Reusable Programs, MIT Press.
McCaffrey, A. J. (2011). The obscure features hypothesis for innovation: One key to improving human innovation. Unpublished doctoral dissertation, University of Massa- chusetts Amherst.
Miller, G. A. (1995). WordNet: A lexical database for Eng- lish. Communications of the ACM, 38(11), 39-41.
Murphy, G. L., & Medin, D. L. (1985). The role of theories in conceptual coherence. Psychological Review, 92, 289- 316.
Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1998). The University of South Florida word association, rhyme, and word fragment norms.
Spector, L. (2008). Introduction to the special issue on Genetic Programming for human-competitive designs. In AI-EDAM: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 22(3), 183-184.
Watts, D. J. (1999). Small worlds: The dynamics of net- works between order and randomness, Princeton Univer- sity Press.
Links
Full Text
http://iccc11.cua.uam.mx/proceedings/the_helpful/mccaffrey_iccc11.pdf
