ALGORITHM (Genetic
| Collection | International Encyclopedia of Systems and Cybernetics |
|---|---|
| Year | 2004 |
| Vol. (num.) | 2(1) |
| ID | ◀ 76 ▶ |
| Object type | Methodology or model |
- “A stochastic, iterative , evolutionary general purpose search strategy based on the principles of population genetics and natural selection ”.
The genetic algorithm was proposed by J.W. HOLLAND (1975, 1992) as a way to the simulation of adaptive population systems. He generalized it as “genetic operators ” models that can be used for the study of optimization problems and more recently for automata learning .
The genetic algorithm, not being narrowly deterministic , does not lead to just a simple solution , but on the contrary opens the way for a progressive and adaptive search for better solutions in evolving conditions.
HOLLAND distinguishes the following transforming operations: crossing-over, inversion, mutation , selection .
These operations are found in nature. But they are frequent in any system wherein numerous agents act collectively as a population engaged in an adaptive search.
A. AGAPIE writes: “Genetic algorithms (GAS) are robust probabilistic algorithms for optimization, relying strongly on parallel computation . their power comes from multi-point exploiting of the searching space ”(2000, p. 35)
See also
Neural networks, Parallel distributed processing