- author = "William B. Langdon and Wolfgang Banzhaf",
- title = "Long-Term Evolution Experiment with Genetic Programming",
- journal = "Artificial Life",
- year = "2022",
- volume = "28",
- number = "2",
- pages = "173--204",
- month = "Summer",
- note = "Invited submission to Artificial Life Journal special issue of the ALIFE'19 conference",
- keywords = "genetic algorithms, genetic programming, GA, GP, convergence, extended unlimited evolution, information theory limit on complexity",
- ISSN = "1064-5462",
- publisher = "MIT Press",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2022_ALJ.pdf",
-
DOI = "
doi:10.1162/artl_a_00360",
-
video_url = "
https://youtu.be/xfJtsWiM7Oo",
-
video_url = "https://youtu.be/TssAIo-vatE",
-
code_url = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/GPavx.tar.gz",
- size = "40 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 = "Journal extension of \cite{Langdon:2019:alife}
Two page summary in \cite{langdon:2022:GECCOhop_alj}
Code http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/GPavx.tar.gz",
