- author = "Penousal Machado and Andre Dias and Amilcar Cardoso",
- title = "{GenCo}: A project report",
- booktitle = "ISAS 2001 -- International Symposium on Adaptive Systems -- Evolutionary Computation and Probabilistic Graphical Models",
- year = "2002",
- editor = "Alberto Ochoa Rodriguez",
- address = "Havana, Cuba",
- month = "19-23 " # mar,
- email = "machado@dei.uc.pt, adias@student.dei.uc.pt, amilcar@dei.uc.pt",
- keywords = "genetic algorithms, genetic programming, NEvAr",
- citeseer-isreferencedby = "oai:CiteSeerPSU:80970",
- citeseer-references = "oai:CiteSeerPSU:276822; \cite{oai:CiteSeerPSU:336117}; oai:CiteSeerPSU:327061; oai:CiteSeerPSU:15714",
- annote = "The Pennsylvania State University CiteSeer Archives",
- language = "en",
- oai = "oai:CiteSeerPSU:510392",
- rights = "unrestricted",
-
URL = "
http://eden.dei.uc.pt/~machado/research/pdf/2001/ISAS-2001.pdf",
-
URL = "
http://citeseer.ist.psu.edu/510392.html",
- size = "6 pages",
- abstract = "Genetic Programming involves the evolution of computer programs, which are usually represented by trees composed by functions and terminals. In order to assign fitness, one must evaluate the programs, which is the most time demanding step of GP. In nowadays standard approaches, the evaluation involves an interpretation step. To avoid this step, which significantly slows the algorithm, some researchers evolve, directly, machine code programs. An alternative approach is to build a Genome Compiler, i.e. a system that transforms the individual's trees in machine-code programs and executes this code. Both techniques can bring huge speed improvements. However, these approaches have some shortcomings. In this paper we present GenCo: a research project whose main goal is development of a Genetic Programming Genome Compiler system, that overcomes some of the drawbacks of current approaches, enabling high speed improvements in a wider range of domains. We will also present experimental results in a programmatic compression task, in which GenCo was, on average, 80 times faster than a standard C based GP system.",
-
notes = "'intron detection, optimization and caching'
cites \cite{fukunaga:1998:gchpGP}
context of the International Conference CIMAF 2001.
Not verified
LilGP \cite{zonger:1996:lilgp} interpretation step replaced by a compilation step. Lena image compression. Claims in the region of 100000 to 1 million individuals evaluated per second GPops.
",
