| Title |
Defining and simulating open-ended novelty: requirements, guidelines, and challenges
|
|---|---|
| Published in |
Theory in Biosciences, May 2016
|
| DOI | 10.1007/s12064-016-0229-7 |
| Pubmed ID | |
| Authors |
Wolfgang Banzhaf, Bert Baumgaertner, Guillaume Beslon, René Doursat, James A. Foster, Barry McMullin, Vinicius Veloso de Melo, Thomas Miconi, Lee Spector, Susan Stepney, Roger White |
| Abstract |
The open-endedness of a system is often defined as a continual production of novelty. Here we pin down this concept more fully by defining several types of novelty that a system may exhibit, classified as variation, innovation, and emergence. We then provide a meta-model for including levels of structure in a system's model. From there, we define an architecture suitable for building simulations of open-ended novelty-generating systems and discuss how previously proposed systems fit into this framework. We discuss the design principles applicable to those systems and close with some challenges for the community. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 66 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 21% |
| Student > Ph. D. Student | 12 | 18% |
| Professor | 9 | 14% |
| Student > Master | 4 | 6% |
| Other | 3 | 5% |
| Other | 10 | 15% |
| Unknown | 14 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 36% |
| Agricultural and Biological Sciences | 6 | 9% |
| Physics and Astronomy | 3 | 5% |
| Social Sciences | 3 | 5% |
| Business, Management and Accounting | 2 | 3% |
| Other | 11 | 17% |
| Unknown | 17 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 October 2023.
All research outputs
#5,515,102
of 25,621,213 outputs
Outputs from Theory in Biosciences
#44
of 218 outputs
Outputs of similar age
#87,308
of 350,261 outputs
Outputs of similar age from Theory in Biosciences
#2
of 6 outputs
Altmetric has tracked 25,621,213 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 218 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 350,261 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.