*CFP: **Tenth Anniversary of Geometric Semantic Genetic Programming*
SpecialIssue of /Genetic Programming and Evolvable Machines/
[Ful
<http://static.springer.com/sgw/documents/1640916/application/pdf/GENP+-+CFP+-+Integrating+Numerical+Optimization+Methods+with+Genetic+Programming.pdf>l
CFP on the Journal's Springer site
<https://www.springer.com/journal/10710/updates/23957712>]
_Guest Editors
_
Alberto Moraglio, University of Exeter, UK, a.moraglio@exeter.ac.uk
Krzysztof Krawiec, Poznan University of Technology, Poland,
krzysztof.krawiec@cs.put.poznan.pl
Colin Johnson, University of Nottingham, UK, Colin.Johnson@nottingham.ac.uk
_About this Issue_
Geometric Semantic Genetic Programming (GSGP) is a form of Genetic
Programming which is guaranteed to see a simple unimodal fitness
landscape with constant slope for any supervised machine learning task.
It was derived using a rigorous geometric theory of representations and
search operators combined with the notion of semantics of programs. In
GSGP, crossover and mutation have special semantic properties: offspring
programs are guaranteed to have behaviour intermediate to their
parents', and mutant programs' behaviour is guaranteed to be similar to
that of the original program. The theory of GSGP reveals a simple
genotype-phenotype map between syntax and semantics of programs, leads
to simple syntactic implementations of these semantic search operators,
and provides a rigorous explanatory framework for its superior runtime
performance.
Since its inception in 2012 [1], GSGP has been rapidly and widely
adopted by the Genetic Programming community at large: it has been
studied, both theoretically and empirically, successfully adopted in
many real-world application domains, improved and extended in many ways,
and led to a plethora of research publications by many research groups
worldwide.
We aim to celebrate the 10th anniversary of GSGP with a special issue
that consolidates and organises the ten years of work on GSGP by the
research community, and fosters further growth of this research area. We
envision that the special issue will cover a historical development of
the field and related areas, report on latest research as well as
identify challenges and reflections about future directions.
_References_
[1] Moraglio A., Krawiec K., Johnson C.G. (2012) Geometric Semantic
Genetic Programming. In: Coello C.A.C., Cutello V., Deb K., Forrest S.,
Nicosia G., Pavone M. (eds) Parallel Problem Solving from Nature - PPSN
XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer,
Berlin, Heidelberg
_Topics of Interest_
We would like to have three main types of submissions that help us, in
various ways, to recount the past, present and future of GSGP: papers
covering the past 10 years (surveys), papers covering the present
(research papers), and papers covering the future (white papers
outlining challenges and opportunities). Topics of interest may include
but are not limited to:
● Program domains (e.g., Boolean, Classification, Arithmetic,
Programs, Neural Networks)
● Improved semantic operators, new semantic operators, approximate
semantic operators, self-adaptive semantic operators
● Efficient implementations, parallel implementations,
implementations on dedicated hardware
● Mathematical analysis and runtime analysis
● Studies on generalisation and effect of noise
● Real world applications and experimental benchmarking
● Algorithmic extensions (e.g., hybridisation with local search,
multi-objective, diversity mechanisms)
● New methods derived or inspired by GSGP
_Important Dates_
Submission deadline: 1 May 2023
Initial reviews: 15 June 2023
Resubmissions: 15 July 2023
Final notifications: 1 September 2023
_Submissions and Review Procedures_
Special Issues are handled in the normal way via the online Editorial
Manager system found athttps://genp.edmgr.com <https://genp.edmgr.com/>.
When uploading your manuscript, select "Special Issue for the Tenth
Anniversary of Geometric Semantic Genetic Programming" in the Collection
menu under the Details tab. Special Issue articles should fulfil all the
standard requirements of any GPEM article. Authors should note that the
same criteria apply to articles in Special Issues as to regular
articles. All papers will undergo the same rigorous GPEM review
process. Please refer to the GPEM website for detailed instructions on
paper submission:http://www.springer.com/10710
<http://www.springer.com/10710>
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