Maximum Individual Complexity is Indefinitely Scalable in Geb
- Submitting institution
-
University of Keele
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 356
- Type
- D - Journal article
- DOI
-
10.1162/artl_a_00285
- Title of journal
- Artificial Life
- Article number
- -
- First page
- 134
- Volume
- 25
- Issue
- 2
- ISSN
- 1064-5462
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2019
- URL
-
https://www.mitpressjournals.org/doi/full/10.1162/artl_a_00285
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
0
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The Geb evolutionary system underpins 20 years of research and many advances in open-ended evolution (e.g. https://doi.org/b74rxr). This paper is the first demonstration of a computational open-ended evolutionary system exhibiting indefinitely-scalable complexity akin to nature. Recordings from the Third Workshop on Open-Ended Evolution (https://workshops.alife.org/oee3/) evidence its importance to the community (e.g. Stanley, Open-endedness Team Leader at OpenAI: “really interesting results”; Packard, cofounder European Centre for Living Technology and ProtoLife S.r.l. / Daptics Inc.: “loved seeing”, “evidence for a certain kind of open-endedness”). The paper has been cited by fellow world leaders in open-ended evolution and open-ended AI (e.g. https://doi.org/fd59, https://arxiv.org/abs/1905.10985).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -