Historical milestone · 1975
Adaptation in Natural and Artificial Systems
Reviewed through September 18, 2026
1975 · Historical milestone
Adaptation in Natural and Artificial Systems
- Era
- 1970s
- Theme
- Machine-learning foundations
- Evidence form
- Formalized genetic algorithms using selection, crossover, mutation, and schemata over populations of candidate solutions
- School / paradigm
- Evolutionary computation
- Institution / context
- University of Michigan
- Researchers
- John Holland
Researcher index
John Holland
Evolutionary computation · University of Michigan
Genetic algorithms
Why it still matters. Established population-based adaptive search.
Representative source for this researcher — not necessarily the source of this milestone: https://mitpress.mit.edu/9780262581110/adaptation-in-natural-and-artificial-systems/ (opens in a new tab)
Understand
Plain-language record, transferred from the reviewed source module.
Theory or experimental setup. Established an optimization and learning paradigm based on population search rather than gradients.
Result / historical claim. Search can be sample-inefficient and sensitive to representation, fitness design, and premature convergence.
Apply
Professional implication, only where the reviewed record states one.
The checked-in record does not state a separate professional application for this entry. The topic page places it in the wider research lineage: .
Verify
Evidence status, stated limitations, and the external sources this record actually carries.
Evidence form. Formalized genetic algorithms using selection, crossover, mutation, and schemata over populations of candidate solutions
Limitation / debate. Evolution strategies, automated architecture search, population-based training, and open-ended agents.
Source status. This milestone row does not carry a primary-source URL in the approved export, and we do not have a verified link for it in our own research. We do not guess one.
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Reproduce
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Cite or share
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