Inheritance Genetic Algorithm

See: Reinforcement, Genetic Algorithm, Mating, Mutation (Genetic Algorithm), Biology, Mutation, Gene, Generation, Selection (Genetic Algorithm), Fitness Function, Artificial Intelligence: A Modern Approach, Chromosome.

References

(Wikipedia, 2018) ⇒ https://en.wikipedia.org/wiki/Inheritance_(genetic_algorithm) Retrieved:2018-6-24.
- In genetic algorithms, inheritance is the ability of modeled objects to mate, mutate (similar to biological mutation), and propagate their problem solving genes to the next generation, in order to produce an evolved solution to a particular problem. The selection of objects that will be inherited from in each successive generation is determined by a fitness function, which varies depending upon the problem being addressed.^[1]
  The traits of these objects are passed on through chromosomes by a means similar to biological reproduction. These chromosomes are generally represented by a series of genes, which in turn are usually represented using binary numbers. This propagation of traits between generations is similar to the inheritance of traits between generations of biological organisms. This process can also be viewed as a form of reinforcement learning, because the evolution of the objects is driven by the passing of traits from successful objects which can be viewed as a reward for their success, thereby promoting beneficial traits.^[1]

↑ ^{Jump up to: 1.0} ^1.1 Russell, Stuart J.; Norvig, Peter (1995). Artificial Intelligence: A Modern Approach. Englewood Heights, NJ: Prentice-Hall.