Output details
11 - Computer Science and Informatics
University of York
Article title
Artificial Biochemical Networks : Evolving Dynamical Systems to Control Dynamical Systems
Type
D - Journal article
Title of journal
IEEE Transactions on Evolutionary Computation
Article number
-
Volume number
PP
Issue number
99
First page of article
n/a
ISSN of journal
1089-778X
Year of publication
2012
Number of additional authors
6
Additional information
<22>Originality:
This combines artificial genetic networks and artificial metabolic networks for the first time, to produce a robot controller based on a relatively natural dynamical systems behaviour.
Significance:
This helps combine and unify various bio-inspired network computational approaches. Subsequent work by the authors has helped expose the common connectionist architecture of multiple such paradigms.
Rigour:
The paper includes rigorous statistics, and dynamical systems analysis of reconstructing the attractor, to analyse the results.
Interdisciplinary
Yes
Cross-referral requested
-
Research group
I - Non-Standard Computation
Citation count
-
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
