Computer Science Journals Catalogue - Taylor & Francis
Computer Science Journals Catalogue - Taylor & Francis
Computer Science Journals Catalogue - Taylor & Francis
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Argument & Computation<br />
Editors: Chris Reed, University of Dundee, UK,<br />
Floriana Grasso, University of Liverpool, UK,<br />
Iyad Rahwan, Masdar Institute of <strong>Science</strong> &<br />
Technology, UAE and Massachusetts Institute of<br />
Technology, USA and Guillermo Simari, University<br />
Nacional del Sur, Argentina<br />
Print ISSN 1946-2166 • Online ISSN 1946-2174<br />
Argument & Computation aims to promote the<br />
interaction and crossfertilisation between the<br />
fields of argumentation theory and computer<br />
science. It will be of interest to researchers in<br />
the fields of artificial intelligence, multi-agent<br />
systems, computer science, logic, philosophy,<br />
argumentation theory, psychology, cognitive<br />
science, game theory and economics. The<br />
journal will accept full articles, describing<br />
novel theoretical or applied research in any<br />
of the areas of interest; reviews, condensing<br />
and critiquing an appropriate subfield of<br />
research; system descriptions, focusing on<br />
implementations (typically offering online<br />
access or downloadable code) and letters,<br />
providing pithy polemic on burning issues.<br />
www.tandf.co.uk/journals/tarc<br />
Applied Artificial<br />
Intelligence<br />
Editor-in-Chief: Robert Trappl, Austrian Research<br />
Institute for Artificial Intelligence, Austria<br />
Print ISSN 0883-9514 • Online ISSN 1087-6545<br />
Published in cooperation with the Austrian<br />
Society for Cybernetic Studies, Applied<br />
Artificial Intelligence addresses concerns in<br />
applied research and applications of artificial<br />
intelligence (AI). The journal also acts as a<br />
medium for exchanging ideas and thoughts<br />
about impacts of AI research. Articles highlight<br />
advances in uses of AI systems for solving<br />
tasks in management, industry, engineering,<br />
administration, and education; evaluations of<br />
existing AI systems and tools, emphasizing<br />
comparative studies and user experiences; and<br />
the economic, social, and cultural impacts of AI.<br />
www.tandf.co.uk/journals/uaai<br />
Behaviour & Information<br />
Technology<br />
Editor-in-Chief: Ahmet Cakir, ERGONOMIC<br />
Institute, Germany<br />
Print ISSN 0144-929X • Online ISSN 1362-3001<br />
Behaviour & Information Technology (BIT)<br />
focuses on the human aspects of information<br />
technology, on which much of our developed<br />
world depends. Information technology<br />
extends beyond the internet and World Wide<br />
Web, and powers telecommunications (both<br />
mobile and fixed), office and industrial systems,<br />
consumer products and entertainment. BIT<br />
reports original research studies and proactive<br />
articles on the design, development, use and<br />
impact of this technology in all its forms and<br />
in all its applications. Papers are fully refereed<br />
and come from a variety of disciplines,<br />
including psychology, ergonomics, computer<br />
science, sociology and management. The<br />
Journal attracts a diverse, international<br />
readership from researchers in universities and<br />
industry, to systems designers and managers.<br />
www.tandf.co.uk/journals/tbit<br />
<strong>Computer</strong> Assisted<br />
Language Learning<br />
Editor: Jozef Colpaert, University of Antwerp,<br />
Belgium<br />
Print ISSN 0958-8221 • Online ISSN 1744-3210<br />
<strong>Computer</strong> Assisted Language Learning (CALL)<br />
is an intercontinental and interdisciplinary<br />
journal which leads the field in its dedication<br />
to all matters associated with the use of<br />
computers in language learning (L1 and L2),<br />
teaching and testing. It provides a forum to<br />
discuss the discoveries in the field and to<br />
exchange experience and information about<br />
existing techniques. The scope of the journal<br />
is intentionally wide-ranging and embraces a<br />
multitude of disciplines.<br />
www.tandf.co.uk/journals/call<br />
<strong>Computer</strong> Methods<br />
in Biomechanics and<br />
Biomedical Engineering<br />
Endorsed by the European Society of Biomechanics<br />
Editors: John Middleton, Cardiff University School<br />
of Dentistry, UK and Christopher R. Jacobs,<br />
Columbia University, USA<br />
Print ISSN 1025-5842 • Online ISSN 1476-8259<br />
The primary aims of the journal are to provide<br />
a means of communicating the advances<br />
being made in the areas of biomechanics and<br />
biomedical engineering, and to stimulate interest<br />
in the continually emerging computer based<br />
technologies which are being applied in these<br />
multidisciplinary subjects. The journal also<br />
provides a focus for the importance of integrating<br />
the disciplines of engineering with medical<br />
technology and clinical expertise, which will have<br />
a major impact on health care in the future.<br />
www.tandf.co.uk/journals/gcmb<br />
<strong>Computer</strong> <strong>Science</strong><br />
Education<br />
Editors: Sally Fincher, University of Kent, UK and<br />
Laurie Murphy, Pacific Lutheran University, USA<br />
Print ISSN 0899-3408 • Online ISSN 1744-5175<br />
<strong>Computer</strong> <strong>Science</strong> Education aims to publish<br />
high-quality papers with a specific focus on<br />
teaching and learning within the computing<br />
discipline that are accessible and of interest to<br />
educators, researchers, and practitioners alike.<br />
www.tandf.co.uk/journals/cse<br />
Connection <strong>Science</strong><br />
Editor-in-Chief: Noel Sharkey, University of<br />
Sheffield, UK<br />
Print ISSN 0954-0091 • Online ISSN 1360-0494<br />
Connection <strong>Science</strong> is an interdisciplinary<br />
scientific and technical journal that has, since<br />
1989, been a focus for research on connectionist<br />
modelling and neural network learning in both<br />
living and artificial systems with an emphasis<br />
on cognition and AI. Papers on these traditional<br />
themes are still strongly encouraged.<br />
However, in response to exciting new work in<br />
evolutionary methods and adaptive robotics,<br />
its scope has been broadened to include<br />
computational research on all biologically<br />
inspired adaptive mechanisms as well as all<br />
areas of biologicallyinspired robotics research.<br />
www.tandf.co.uk/journals/ccos<br />
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