- author = "William B. Langdon and Wolfgang Banzhaf",
- title = "Long-Term Evolution Experiment with Genetic Programming [Hot of the Press]",
- booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference Companion",
- year = "2022",
- editor = "Marcus Gallagher",
- pages = "29--30",
- address = "Boston, USA",
- series = "GECCO '22",
- month = "9-13 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, Information, Theory limit on complexity, Long-Term Evolution Experiment LTEE, extended unlimited evolution, Open Complexity, Speedup technique, information theory limit on complexity",
- isbn13 = "978-1-4503-9268-6/22/07",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_2022_GECCOhop_alj.pdf",
-
DOI = "
doi:10.1145/3520304.3534065",
-
video_url = "
https://vimeo.com/723787742",
-
code_url = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/GPavx.tar.gz",
-
video_url = "https://youtu.be/xfJtsWiM7Oo",
- size = "2 pages",
- abstract = "We evolve floating point Sextic polynomial populations of genetic programming binary trees for up to a million generations. We observe continued innovation but this is limited by their depth and suggest deep expressions are resilient to learning as they disperse information, impeding evolvability and the adaptation of highly nested organisms and instead we argue for open complexity. Programs with more than 2000000000 instructions (depth 20000) are created by crossover. To support unbounded long-term evolution experiments LTEE in GP we use incremental fitness evaluation and both SIMD parallel AVX 512 bit instructions and 16 threads to yield performance equivalent of up to 1.1 trillion GP operations per second, 1.1 tera GPops, on an Intel Xeon Gold 6136 CPU 3.00GHz server.",
-
notes = "Summary of \cite{Langdon:2022:ALJ} Slides:
http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2022/langdon_2022_GECCOhop_alj_slides.pdf
ACM id: 12519.411
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
