NDLI: Open issues in genetic programming

Content Provider	Springer Nature Link
Author	O’Neill, Michael Vanneschi, Leonardo Gustafson, Steven Banzhaf, Wolfgang
Copyright Year	2010
Abstract	It is approximately 50 years since the first computational experiments were conducted in what has become known today as the field of Genetic Programming (GP), twenty years since John Koza named and popularised the method, and ten years since the first issue appeared of the Genetic Programming & Evolvable Machines journal. In particular, during the past two decades there has been a significant range and volume of development in the theory and application of GP, and in recent years the field has become increasingly applied. There remain a number of significant open issues despite the successful application of GP to a number of challenging real-world problem domains and progress in the development of a theory explaining the behavior and dynamics of GP. These issues must be addressed for GP to realise its full potential and to become a trusted mainstream member of the computational problem solving toolkit. In this paper we outline some of the challenges and open issues that face researchers and practitioners of GP. We hope this overview will stimulate debate, focus the direction of future research to deepen our understanding of GP, and further the development of more powerful problem solving algorithms.
Starting Page	339
Ending Page	363
Page Count	25
File Format	PDF
ISSN	13892576
Journal	Genetic Programming and Evolvable Machines
Volume Number	11
Issue Number	3-4
e-ISSN	15737632
Language	English
Publisher	Springer US
Publisher Date	2010-05-14
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Open issues Genetic programming Biomedical Engineering Programming Languages, Compilers, Interpreters Programming Techniques Software Engineering/Programming and Operating Systems Artificial Intelligence (incl. Robotics) Electrical Engineering
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computer Science Applications Software Hardware and Architecture

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