Genetic Algorithms + Data Structures = Evolution Programs

By Z. Michalewicz. Springer Berlin Heidelberg, 2000

610 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/7be0e2026fd9d4cd674347bd4f472baed95275d9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Andrew Campen
2. A. Keith Dunker
3. Jingwei Meng
4. Ryan M. Williams
5. Vladimir N Uversky
6. C. Brown

Citations in the corpus

• Learning Complexity-Bounded Rule-Based Classifiers by Combining. Association Analysis and Genetic Algorithms (2005, neutral): “5) [11].”
• TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder. (2008, methodology): “Specifically, both a Canonical Genetic Algorithm (CGA) [31] and a Stochastic Hill Climbing Algorithm (SHCA) [32] were tested.”