Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research.
The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following:
cognitive science
games
learning
knowledge representation
memory and neural system modelling
perception
problem-solving
All submitted manuscripts are subject to initial appraisal by the Editor-in-Chief, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees. All peer review is double anonymized and submission is online.
Proposals for special issues in cutting-edge areas of AI should be discussed with the Editor-in-Chief.
Queries regarding submissions can be made by contacting the Editor-in-Chief, whose decision is final.
Journal metrics
Usage
60K annual downloads/views
Citation metrics
1.7 (2023) Impact Factor
1.8 (2023) 5 year IF
6.1 (2023) CiteScore (Scopus)
Q1 CiteScore Best Quartile
0.708 (2023) SNIP
0.511 (2023) SJR
Speed/acceptance
102 days avg. from submission to first
decision
234 days avg. from submission to first
post-review decision
13 days avg. from acceptance to online
publication
4% acceptance rate
Understanding and using journal metrics
Journal metrics can be a useful tool for readers, as well as for authors
who are deciding where to submit their next manuscript for publication.
However, any one metric only tells a part of the story of a journal’s
quality and impact. Each metric has its limitations which means that it
should never be considered in isolation, and metrics should be used to
support and not replace qualitative review.
We strongly recommend that you always use a number of metrics, alongside
other qualitative factors such as a journal’s aims & scope, its
readership, and a review of past content published in the journal. In
addition, a single article should always be assessed on its own merits and
never based on the metrics of the journal it was published in.
Usage and acceptance rate data above are for the last full calendar year
and are updated annually in February. Speed data is updated every six
months, based on the prior six months. Citation metrics are updated
annually mid-year. Please note that some journals do not display all of
the following metrics
(find out why).
Usage:
the total number of times articles in the journal were viewed by users
of Taylor & Francis Online in the previous calendar year, rounded to the
nearest thousand.
Citation Metrics
Impact Factor*:
the average number of citations received by articles published in the
journal within a two-year window. Only journals in the Clarivate Science
Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI),
Arts and Humanities Citation Index (AHCI) and the Emerging Sources
Citation Index (ESCI) have an Impact Factor.
Impact Factor Best Quartile*:
the journal’s highest subject category ranking in the Journal Citation
Reports. Q1 = 25% of journals with the highest Impact Factors.
5 Year Impact Factor*:
the average number of citations received by articles in the journal
within a five-year window.
CiteScore (Scopus)†:
the average number of citations received by articles in the journal over
a four-year period.
CiteScore Best Quartile†:
the journal’s highest CiteScore ranking in a Scopus subject category. Q1
= 25% of journals with the highest CiteScores.
SNIP
(Source Normalized Impact per Paper):
the number of citations per paper in the journal, divided by citation
potential in the field.
SJR
(Scimago Journal Rank):
Average number of (weighted) citations in one year, divided by the
number of articles published in the journal in the previous three years.
Speed/acceptance
From submission to first decision:
the average (median) number of days for a manuscript submitted to the
journal to receive a first decision. Based on manuscripts receiving a
first decision in the last six months.
From submission to first post-review decision:
the average (median) number of days for a manuscript submitted to the
journal to receive a first decision if it is sent out for peer review.
Based on manuscripts receiving a post-review first decision in the last
six months.
From acceptance to online publication:
the average (median) number of days from acceptance of a manuscript to
online publication of the Version of Record. Based on articles published
in the last six months.
Acceptance rate:
articles accepted for publication by the journal in the previous
calendar year as percentage of all papers receiving a final decision.
Editor-in-Chief: Eric Dietrich -Department of Philosophy, State University of New York, Binghamton, USA email: [email protected]
Deputy Editors-in-Chief: Filippo Fabrocini -Sustainable AI Lab Tongji University, College of Design and Innovation, China Antonio Lieto -Department of Computer Science, University of Turin, Italy
Managing Editor: Tara Hall -State University of New York, Binghamton, USA
Editorial Board: Grigoris Antoniou -University of Huddersfield, UK Cristiano Castelfranchi -ISTC-CNR, Italy Sanjit Chakraborty -Indian Institute of Science Education and Research Kolkata, India David Corne -Heriot-Watt University, UK Rick Dale -University of Memphis, USA Jim Davies -Carleton University, Canada Thomas Eskridge -Harris Institute for Assured Information, Florida Institute of Technology, USA Jean-Gabriel Ganascia -Pierre and Marie Curie University, France Tracy Hammond -Texas A&M University, USA Henry Hexmoor -Southern Illinois University at Carbondale, USA Kyung-Joong Kim -Sejong University, South Korea Natalio Krasnogor -Newcastle University, UK Catherine Legg -University of Waikato, New Zealand Klaus Mainzer -Technical University of Munich, Germany Stacy Marsella -Northeastern University, USA Jim Marshall -Sarah Lawrence College, USA John-Jules Meyer -Utrecht University, Netherlands Ramesh K. Mishra -University of Hyderabad, India Riichiro Mizoguchi -Osaka University, Japan Sara Moein -Washington University, USA Nasser Mozayani -Iran University of Science and Technology, Iran Slawomir J. Nasuto -University of Reading, UK Fabio Paglieri -ISTC-CNR, Italy Rose Paradis -Lockheed Martin, USA Henry Prakken -Utrecht University, Netherlands Anita Raja -University of North Carolina at Charlotte, USA Ashwin Ram -Xerox PARC, USA Zbigniew W. Ras -University of North Carolina, USA Eugene Santos -Dartmouth College, USA Inayatullah Shah -King Saud University, Saudi Arabia S.J. Shyu -Ming Chuan University, Taiwan Suresh Sundaram -Nanyang Technological University, Singapore Chris Thornton -University of Sussex, UK Schiaffonati Viola -Polytechnic University of Milan, Italy Toby Walsh -University of New South Wales, Australia Di Wang -EBTIC, UAE Alan Winfield -University of the West of England, UK I-Chen Wu -National Chiao Tung University, Taiwan Qizhi Xu -Beijing Institute Of Technology, China Bo Yuan -Shanghai Jiao Tong, China Mengjie Zhang -Victoria University of Wellington, New Zealand Jin Zheng -Beihang University, China Zhi-Hua Zhou -Nanjing University, China
Abstracting and indexing
The Journal of Experimental & Theoretical Artificial Intelligence is indexed in:
ACM Digital Library British Library CLOCKSS CrossRef DBLP Computer Science Bibliography (University of Trier) EBSCO - Applied Science & Technology Source EBSCO - Academic Search Complete EBSCO - STM Source Ei Compendex/ Engineering Village (Elsevier) E-LIB (University of Bremen) Excellence in Research for Australia (ERA) Google Scholar Inspec (The IET) Microsoft Academic Naver Corporation Portico ProQuest - ProQuest Central ProQuest - SciTech Premium Collection ProQuest - Technology Collection PsycINFO (American Psychological Association) SAO/NASA Astrophysics Data System Abstract Service Science Citation Index Expanded (Thomson Reuters) Scopus (Elsevier) Ulrich's Periodicals Directory Web of Science (Thomson Reuters) WorldCat Local (OCLC) zbMATH Zetoc
Open access
Journal of Experimental & Theoretical Artificial Intelligence is a hybrid open access journal that is part of our Open Select publishing program, giving you the option to publish open access. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research.
Why choose open access?
Increase the discoverability and readership of your article
Make an impact and reach new readers, not just those with easy access to a research library
Freely share your work with anyone, anywhere
Comply with funding mandates and meet the requirements of your institution, employer or funder
Rigorous peer review for every open access article
Article Publishing Charges (APC)
If you choose to publish open access in this journal you may be asked to pay an Article Publishing Charge (APC). You may be able to publish your article at no cost to yourself or with a reduced APC if your institution or research funder has an open access agreement or membership with Taylor & Francis.
Members of the following groups can receive an individual print subscription to Journal of Experimental & Theoretical Artificial Intelligence at a special society member rate. Please see the pricing or subscribe page for details.
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