- author = "Ibrahim Kushchu",
- title = "An Evaluation of Evolutionary Generalisation in Genetic Programming",
- journal = "Artificial Intelligence Review",
- year = "2002",
- volume = "18",
- number = "1",
- pages = "3--14",
- month = sep,
- keywords = "genetic algorithms, genetic programming, learning, robustness",
-
DOI = "
doi:10.1023/A:1016379201230",
- abstract = "Generalisation is one of the most important performance evaluation criteria for artificial learning systems. An increasing amount of research has recently concentrated on the robustness or generalisation ability of the programs evolved using Genetic Programming (GP). While some of these researchers report on the brittleness of the solutions evolved, some others propose methods of promoting robustness/generalisation. In this paper, a review of research on generalisation in GP and problems with brittleness of solutions produced by GP is presented. Also, a brief overview of several new methods promoting robustness/generalisation of the solutions produced by GP are presented.",
-
notes = "Article ID: 405648
Note author previously spelt name as I Kuscu",
