- author = "Tony E. Lewis and George D. Magoulas",
- title = "TREAD: A new genetic programming representation aimed at research of long term complexity growth",
- booktitle = "GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation",
- year = "2008",
- editor = "Maarten Keijzer and Giuliano Antoniol and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Nikolaus Hansen and John H. Holmes and Gregory S. Hornby and Daniel Howard and James Kennedy and Sanjeev Kumar and Fernando G. Lobo and Julian Francis Miller and Jason Moore and Frank Neumann and Martin Pelikan and Jordan Pollack and Kumara Sastry and Kenneth Stanley and Adrian Stoica and El-Ghazali Talbi and Ingo Wegener",
- isbn13 = "978-1-60558-130-9",
- pages = "1339--1340",
- address = "Atlanta, GA, USA",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2008/docs/p1339.pdf",
-
DOI = "
doi:10.1145/1389095.1389353",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- month = "12-16 " # jul,
- keywords = "genetic algorithms, genetic programming, artificial intelligence, representations: Poster, TREAD",
- abstract = "Several forms of computer program (or representation) have been proposed for Genetic Programming (GP) systems to evolve, such as linear, tree based or graph based. Typically, GP representations are highly effective during the initial search phases of evolution but stagnate before deep levels of complexity are acquired. A new representation, TREAD, is proposed to combine aspects of flow of execution and flow of data systems. The distinguishing features of TREAD are designed for researching improvements to the long term acquisition of novel features in GP (at the expense of the speed of the initial search if necessary). TREAD is validated on a symbolic regression problem and is found to be capable of successfully developing solutions through artificial evolution.",
-
notes = "GECCO-2008 A joint meeting of the seventeenth
international conference on genetic algorithms
(ICGA-2008) and the thirteenth annual genetic
programming conference (GP-2008).
ACM Order Number 910081. Also known as \cite{1389353}
PADO \cite{teller:1995:PADO}. Data flow, flow of execution. PDGP.",
