Abstract
This article discusses how restructured incentives could have inhibited innovation in ancient China and explain the Needham paradox. Agents in a genetic algorithmic game maximize their payoffs by choosing between innovating and studying the Classics. By restructuring incentives toward studying the Classics, initial spurts of innovation are smothered, resulting in a population with all agents studying the Classics. The incentive structure has a statistically and quantitatively significant impact on the expected average payoffs and the strategy profile of the population: the average payoffs for a regime which rewards innovation fluctuate more but are always higher and the strategy profile is varied.
| Original language | English |
|---|---|
| Pages (from-to) | 18-28 |
| Number of pages | 11 |
| Journal | Complexity |
| Volume | 18 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Free Keywords
- Economic history
- Evolutionary game
- Genetic algorithm
- Needham paradox
ASJC Scopus subject areas
- General Computer Science
- General
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