Recognizing the new
a multi-agent model of analogy in strategic decision-making
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Author
Contributions
- Warglien, Massimo - Contributor
- Harvard Business School - Contributor
Publication
2008 - Harvard Business School, Boston, Massachusetts
Language
English
Word Count
12,500 words, Guess
Page Count
50 pages
Identifiers
- OCLC Control Number226282277
- Open LibraryOL48042298M
Description
In novel environments, strategic decision-making is often premised on analogy, and recognition lies at its heart. Recognition refers to a class of cognitive processes through which a problem is interpreted associatively in terms of something that has been experienced in the past. Despite recognition's centrality to strategic choice, we have limited knowledge of its nature and its influence on strategic decision-making in individuals, much less in the multi-agent settings in which these decisions typically occur. In this paper, we develop a model that extends neural nets techniques to capture recognition processes in groups of decision-makers. We use the model to derive some fundamental properties of collective recognition.
Subjects
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