Created by W.Langdon from gp-bibliography.bib Revision:1.4009

@Article{daida:2001:GPEM, author = "Jason M. Daida and Robert R. Bertram and Stephen A. Stanhope and Jonathan C. Khoo and Shahbaz A. Chaudhary and Omer A. Chaudhri and John A. {Polito II}", title = "What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming", journal = "Genetic Programming and Evolvable Machines", year = "2001", volume = "2", number = "2", pages = "165--191", month = jun, keywords = "genetic algorithms, genetic programming, problem difficulty, test problems, fitness landscapes, GP theory", ISSN = "1389-2576", broken = "http://ipsapp009.lwwonline.com/content/getfile/4723/5/5/fulltext.pdf", DOI = "doi:10.1023/A:1011504414730", abstract = "This paper addresses the issue of what makes a problem genetic programming (GP)-hard by considering the binomial-3 problem. In the process, we discuss the efficacy of the metaphor of an adaptive fitness landscape to explain what is GP-hard. We indicate that, at least for this problem, the metaphor is misleading.", notes = "patched lilgp. Mersenne Twister. Size and Shape of solutions to 3 binomial - tunably difficult by changing random constants used. Edvard Munch Scream. Inconsistency of ERC value within parse tree context. Destructive crossover. P180 {"}the fitness function did not need to be rugged for GP to encounter difficulty.{"} GP as error correcting. Mathematica. p186 {"}increased population meant more individuals gathered around the{"} suboptimal {"}0.8 attractor{"}. Article ID: 335714", }

Genetic Programming entries for Jason M Daida Robert R Bertram Stephen A Stanhope Jonathan C Khoo Shahbaz A Chaudhary Omar A Chaudhri John A Polito 2