scholar.google.com › citations
Fitness landscapes and difficulty in genetic programming - IEEE Xplore
ieeexplore.ieee.org › document
The structure of the fitness landscape on which genetic programming operates is examined. The landscapes of a range of problems of known difficulty are ...
Abstract-The structure of the fitness landscape on which genetic programming operates is examined. The landscapes of a range of problems of known difficulty ...
The structure of the fitness landscape on which genetic programming operates is examined. The landscapes of a range of problems of known difficulty are ...
In the case of Genetic Programming, defining and handling fitness landscapes is a particularly hard task, given the complexity of the structures being evolved ...
Fitness landscape investigated by using GP operators (without selection) on gen=0 to give a number of random walks. Look at autocorrelation of fitness along ...
A fitness landscape consisting entirely of a single hill leading to the global optimum proves to be harder for hillclimbers than GAs.
Missing: Programming. | Show results with:Programming.
K. E. Kinnear. Fitness landscapes and difficulty in genetic programming. In Proceedings of the First IEEE Conference on Evolutionary Computing, pages 142–147.
In the case of Genetic Programming, defining and handling fitness landscapes is a particularly hard task, given the complexity of the structures being evolved ...
People also ask
What is the role of fitness function in a genetic algorithm?
What is the difference between adaptive landscape and fitness landscape?
What is fitness landscape analysis?
What is the fitness score in a genetic algorithm?
For the first time, this chapter rigorously derives a problem hardness measure from a theoretical difficulty measure widely used in complexity theory of EAs.
In the case of Genetic Programming, defining and handling fitness landscapes is a particularly hard task, given the complexity of the structures being evolved ...