- author = "William B. Langdon and Justyna Petke and David Clark",
- title = "Dissipative Polynomials",
- booktitle = "5th Workshop on Landscape-Aware Heuristic Search",
- series = "GECCO 2021 Companion",
- year = "2021",
- editor = "Nadarajen Veerapen and Katherine Malan and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa",
- month = "10-14 " # jul,
- pages = "1683--1691",
- organisation = "SIGEVO",
- address = "Internet",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, information loss, information funnels, entropy, evolvability, mutational robustness, neutral networks, SBSE, software robustness, Correctness Attraction, diversity, software testing, theory of bloat, introns",
- isbn13 = "978-1-4503-8351-6/21/07",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2021_LAHS.pdf",
-
video_url = "
https://youtu.be/Hsj_uLjKaDc",
-
DOI = "
doi:10.1145/3449726.3463147",
-
code_url = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/GPinc.tar.gz",
- size = "9 pages",
- abstract = "Limited precision floating point computer implementations of large polynomial arithmetic expressions are nonlinear and dissipative, they are not reversible (irreversible, lack conservation), lose information, and so are robust to perturbations (anti-fragile) and resilient to fluctuations. This gives a largely stable locally flat evolutionary neutral fitness search landscape. Thus even with a large number of test cases, both large and small changes deep within software typically have no effect and are invisible externally. Shallow mutations are easier to detect but their RMS error need not be simple.",
-
notes = "Slides:
http://www.cs.ucl.ac.uk/staff/W.Langdon/gecco2021/Langdon_2021_LAHS_slides.pdf
Code http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/GPinc.tar.gz
https://sites.google.com/view/lahs-workshop/lahs-2022/lahs-2021
GECCO-2021 A Recombination of the 30th International Conference on Genetic Algorithms (ICGA-2021) and the 26th Annual Genetic Programming Conference (GP-2021)",
