- author = "John R. Koza",
- title = "A Genetic Approach to the Truck Backer Upper Problem and the Inter-Twined Spiral Problem",
- booktitle = "Proceedings of IJCNN International Joint Conference on Neural Networks",
- volume = "IV",
- pages = "310--318",
- year = "1992",
- month = "7-11 " # jun,
- address = "Baltimore, USA",
- publisher_address = "Piscataway, NJ, USA",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, connectionism",
- ISBN = "0-7803-0559-0",
-
URL = "
http://www.genetic-programming.com/jkpdf/ijcnn1992.pdf",
-
DOI = "
doi:10.1109/IJCNN.1992.227324",
- abstract = "ABSTRACT Neural networks are a biologically motivated problem-solving paradigm that has proven successful in robustly solving a variety of problems. This paper describes another biologically motivated paradigm, namely genetic programming, which can also solve a variety of problems. This paper explains genetic programming and applies it to two well-know benchmark problems from the field of neural networks. The truck backer upper problem is a multi-dimensional control problem and the inter-twined spirals problem is a challenging classification problem.",
-
notes = "INSPEC Accession Number: 4422198
IJCNN-92
",
