AI Open is a freely accessible platform to share actionable knowledge and forward-thinking perspectives on the theory of artificial intelligence and its applications. The journal welcomes research articles, review papers, perspectives, short communications and technical notes on all aspects of artificial intelligence and its applications.Topics covered include, but are not limited to:Deep learning and representation learningGraph theory and graph miningConstraints, satisfiability, and searchKnowledge representation, reasoning, and logicMachine learning and data miningKnowledge graph and applicationsAgent-based and multi-agent systemsWeb and knowledge-based information systemsNatural language processingImage processing and analysisUncertaintyBrain-based LearningImplicit Cognition and LearningEditorial Board
Advanced Bionics (ABS) is an international peer-reviewed, open access journal that publishes original research papers, reviews, letters, editorials, highlights, perspectives, comments and news.ABS focuses on the study of novel principles and functions observed in biological systems, as well as the application of this knowledge to address real-world scientific challenges.ABS aims to lead advancements in fundamental bionic research, pushing the boundaries of novel bionic investigations and fostering disruptive technologies within the field. Submissions to the journal are expected to provide fresh insights, possess scientific impact and a high level of quality, as well as contribute to shaping the future of bionic research.As an interdisciplinary journal, ABS covers a wide array of topics, including but not limited to:(1) Bionic Robotics, Electronics, and Intelligent Devices (2) Bio-inspired Artificial Intelligence (3) Biomechanics and Bionic Healthcare Engineering (4) Bio-inspired Functional Surfaces/Interfaces (5) Bio-inspired Functional Materials and Biosensors (6) Bio-inspired Energy System (7) Bio-manufacturing and Bionic Manufacturing (8) Bio-inspired structures and designEditorial Board
The journal of Artificial Intelligence (AIJ) welcomes papers on broad aspects of AI that constitute advances in the overall field including, but not limited to, cognition and AI, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constraint processing, ethical AI, heuristic search, human interfaces, intelligent robotics, knowledge representation, machine learning, multi-agent systems, natural language processing, planning and action, and reasoning under uncertainty. The journal reports results achieved in addition to proposals for new ways of looking at AI problems, both of which must include demonstrations of value and effectiveness.Papers describing applications of AI are also welcome, but the focus should be on how new and novel AI methods advance performance in application areas, rather than a presentation of yet another application of conventional AI methods. Papers on applications should describe a principled solution, emphasize its novelty, and present an indepth evaluation of the AI techniques being exploited.Apart from regular papers, the journal also accepts Research Notes, Research Field Reviews, Position Papers, and Book Reviews (see details below). The journal will also consider summary papers that describe challenges and competitions from various areas of AI. Such papers should motivate and describe the competition design as well as report and interpret competition results, with an emphasis on insights that are of value beyond the competition (series) itself.From time to time, there are special issues devoted to a particular topic. Such special issues must always have open calls-for-papers. Guidance on the submission of proposals for special issues, as well as other material for authors and reviewers can be found at http://aij.ijcai.org/special-issues.Types of PapersRegular PapersAIJ welcomes basic and applied papers describing mature, complete, and novel research that articulate methods for, and provide insight into artificial intelligence and the production of artificial intelligent systems. The question of whether a paper is mature, complete and novel is ultimately determined by reviewers and editors on a case-bycase basis. Generally, a paper should include a convincing motivational discussion, articulate the relevance of the research to Artificial Intelligence, clarify what is new and different, anticipate the scientific impact of the work, include all relevant proofs and/or experimental data, and provide a thorough discussion of connections with the existing literature. A prerequisite for the novelty of a paper is that the results it describes have not been previously published by other authors and have not been previously published by the same authors in any archival journal. In particular, a previous conference publication by the same authors does not disqualify a submission on the grounds of novelty. However, it is rarely the case that conference papers satisfy the completeness criterion without further elaboration. Indeed, even prize-winning papers from major conferences often undergo major revision following referee comments, before being accepted to AIJ.AIJ caters to a broad readership. Papers that are heavily mathematical in content are welcome but should include a less technical high-level motivation and introduction that is accessible to a wide audience and explanatory commentary throughout the paper. Papers that are only purely mathematical in nature, without demonstrated applicability to artificial intelligence problems may be returned. A discussion of the work's implications on the production of artificial intelligent systems is normally expected.There is no restriction on the length of submitted manuscripts. However, authors should note that publication of lengthy papers, typically greater than forty pages, is often significantly delayed, as the length of the paper acts as a disincentive to the reviewer to undertake the review process. Unedited theses are acceptable only in exceptional circumstances. Editing a thesis into a journal article is the author's responsibility, not the reviewers'.Research NotesThe Research Notes section of the Journal of Artificial Intelligence will provide a forum for short communications that cannot fit within the other paper categories. The maximum length should not exceed 4500 words (typically a paper with 5 to 14 pages). Some examples of suitable Research Notes include, but are not limited to the following: crisp and highly focused technical research aimed at other specialists; a detailed exposition of a relevant theorem or an experimental result; an erratum note that addresses and revises earlier results appearing in the journal; an extension or addendum to an earlier published paper that presents additional experimental or theoretical results.ReviewsThe AIJ invests significant effort in assessing and publishing scholarly papers that provide broad and principled reviews of important existing and emerging research areas, reviews of topical and timely books related to AI, and substantial, but perhaps controversial position papers (so-called "Turing Tape" papers) that articulate scientific or social issues of interest in the AI research community.Research Field Reviews: AIJ expects broad coverage of an established or emerging research area, and the articulation of a comprehensive framework that demonstrates the role of existing results, and synthesizes a position on the potential value and possible new research directions. A list of papers in an area, coupled with a summary of their contributions is not sufficient. Overall, a field review article must provide a scholarly overview that facilitates deeper understanding of a research area. The selection of work covered in a field article should be based on clearly stated, rational criteria that are acceptable to the respective research community within AI; it must be free from personal or idiosyncratic bias.Research Field Reviews are by invitation only, where authors can then submit a 2-page proposal of a Research Field Review for confirmation by the special editors. The 2-page proposal should include a convincing motivational discussion, articulate the relevance of the research to artificial intelligence, clarify what is new and different from other surveys available in the literature, anticipate the scientific impact of the proposed work, and provide evidence that authors are authoritative researchers in the area of the proposed Research Field Review. Upon confirmation of the 2-page proposal, the full Invited Research Field Reviews can then be submitted and then undergoes the same review process as regular papers.Book Reviews: We seek reviewers for books received, and suggestions for books to be reviewed. In the case of the former, the review editors solicit reviews from researchers assessed to be expert in the field of the book. In the case of the latter, the review editors can either assess the relevance of a particular suggestion, or even arrange for the refereeing of a submitted draft review.Position Papers: The last review category, named in honour of Alan Turing as a "Turing Tapes" section of AIJ, seeks clearly written and scholarly papers on potentially controversial topics, whose authors present professional and mature positions on all variety of methodological, scientific, and social aspects of AI. Turing Tape papers typically provide more personal perspectives on important issues, with the intent to catalyze scholarly discussion.Turing Tape papers are by invitation only, where authors can then submit a 2-page proposal of a Turing Tape paper for confirmation by the special editors. The 2-page proposal should include a convincing motivational discussion, articulate the relevance to artificial intelligence, clarify the originality of the position, and provide evidence that authors are authoritative researchers in the area on which they are expressing the position. Upon confirmation of the 2-page proposal, the full Turing Tape paper can then be submitted and then undergoes the same review process as regular papers.Competition PapersCompetitions between AI systems are now well established (e.g. in speech and language, planning, auctions, games, to name a few). The scientific contributions associated with the systems entered in these competitions are routinely submitted as research papers to conferences and journals. However, it has been more difficult to find suitable venues for papers summarizing the objectives, results, and major innovations of a competition. For this purpose, AIJ has established the category of competition summary papers.Competition Paper submissions should describe the competition, its criteria, why it is interesting to the AI research community, the results (including how they compare to previous rounds, if appropriate), in addition to giving a summary of the main technical contributions to the field manifested in systems participating in the competition. Papers may be supplemented by online appendices giving details of participants, problem statements, test scores, and even competition-related software.Although Competition Papers serve as an archival record of a competition, it is critical that they make clear why the competition's problems are relevant to continued progress in the area, what progress has been made since the previous competition, if applicable, and what were the most significant technical advances reflected in the competition results. The exposition should be accessible to a broad AI audience.
Artificial Intelligence (AI) techniques are widely used to solve a variety of problems and to optimize the production and operation processes in the fields of agriculture, food and bio-system engineering.Artificial Intelligence in Agriculture is an Open Access journal, publishing original research, reviews and perspectives on the theory and practice of artificial intelligence (AI) in agriculture, food and bio-system engineering and related areas. Artificial Intelligence in Agriculture serves as an interdisciplinary forum to share ideas and solutions related to artificial intelligence and applications in agriculture. The journal welcomes both fundamental science and applied research describing the practical applications of AI methods in the fields of agriculture, food - and bio-system engineering and related areas.Topics of interest to the journal include, but are not limited to:AI-based decision support systemsAI-based precision agricultureSmart sensors and Internet of ThingsAgricultural robotics and automation equipmentAgricultural knowledge-based systemsComputational intelligence in agriculture, food and bio-systemsAI in agricultural optimization managementIntelligent interfaces and human-machine interactionMachine vision and image/signal processingMachine learning and pattern recognitionNeural networks, fuzzy systems, neuro-fuzzy systemsSystems modeling and analysisIntelligent systems for animal feedingExpert systems in agricultureCrop Phenotyping and analysisRemote sensing in agricultureAI technology in aquicultureAI in food engineering and cold chain logisticsBig Data and Cloud ComputingAutomatic navigation and self-driving technologyPrecision agricultural aviationDistributed ledger technology (Blockchain)The journal welcomes original research articles, review articles, perspective papers and short communications. The journal's editorial leadership welcome suggestions and proposals for special issues.Editorial Board
Artificial intelligence (AI) is one of the fastest growing disciplines in electronic information technology. Along with diversified data, AI-enabled technologies such as image processing, smart sensors, and intelligent inversion, are being tested by researchers in a wide variety of geosciences domains. These technologies have the potential to help geosciences move from qualitative to quantitative analysis. We believe that taking an interdisciplinary approach will deliver benefits to both geosciences and AI.Artificial Intelligence in Geosciences is an open access journal providing an interdisciplinary forum where ideas and solutions related to artificial intelligence and its applications in geosciences can be shared and discussed. To support this discussion, we encourage authors to open source their code, data, and the labels used in AI.We welcome both fundamental science and applied research describing the practical applications of AI methods in the fields of geology, rock physics, seismicity, hydrology, ecology, marine geosciences, planetary science, environment, volcanology, oceanography, remote sensing and GIS, and related areas.Submissions to Artificial Intelligence in Geosciences may take the form of original research articles, review articles, perspective papers, or short communications, and a variety of topics will be considered. These include, but are not limited to:AI-based decision support systemsAI-based precision geosciencesSmart sensors and the Internet of ThingsGeosciences robotics and automation equipmentGeosciences knowledge-based systemsComputational intelligence in geosciencesAI in geosciences optimization managementIntelligent interfaces and human-machine interactionMachine vision and image/signal processingMachine learning and pattern recognitionNeural networks, fuzzy systems, neuro-fuzzy systemsSystems modeling and analysisExpert systems in geosciencesBig data and cloud computing in geosciencesAutomatic navigation and self-driving technologyHigh Performance Computing in the context of Machine LearningArtificial Intelligence in Geosciences also welcomes suggestions and proposals for special issues.Editorial Board
Providing a scientific forum for practical applications and theoretical advances of Artificial Intelligence (AI) in the life sciences and related disciplines including (but not restricted to):New AI methods for life science researchAdaptation of existing AI concepts for life science applicationsApplication of AI approaches in: Molecular and systems biologyPopulation and disease geneticsBio- and cheminformaticsMedicinal chemistry, chemical biology, and drug discoveryMedical researchPublications are required to contain substantial AI and life science components. Clinical studies reporting routine diagnostic efforts hall outside the scope of AILSCI.Background: Artificial Intelligence originates from computer science and covers a wide range of approaches intended to enhance the ability of machines to make data-driven decisions and accurate predictions of events. In many scientific fields, AI is being increasingly considered and integrated, especially in the context of Big Data. Given their complexity and highly interdisciplinary nature, the life sciences provide ample opportunities for AI to impact R&D efforts in a variety of ways.Key words: Artificial Intelligence; Life Sciences; Drug Discovery; Bio- and Cheminformatics, Machine Learning; Machine Intelligence; Deep Learning; Data Mining; Big Data.
An official Journal of the Shandong UniversityTo promote advances and original contributions to robotics, biomimetics and artificial intelligence, Biomimetic Intelligence and Robotics (BIROB) provides a platform and forum for the exchange and communication of the most innovative and exciting new discoveries and impactful applications in the fields of biomimetic intelligence and robotics.Biomimetic Intelligence and Robotics (BIROB) publishes original, high-quality, peer-reviewed theoretical and applied research achievements and review articles in the fields of robotics, biomimetics, artificial intelligence, and the innovative integration of them.Topics covered by the journal include but are not limited to: autonomous systems, biomimetic actuators, biomimetic and bio-inspired design, biomimetic materials, biomimetics and artificial intelligence, exoskeletons, field robotics, human-robot interaction, humanoids, industrial robotics, kinematics and dynamics, machine learning, material sciences, medical robotics and technology, motion planning and control, micro and nano robotics, multirobot systems, sensors and bionic sensing, service robotics, and soft robotics.P-ISSN: 2097-0242
Cognitive Robotics merges two research fields, physical systems and control architectures. The physical systems are designed to adapt to dynamic environments while the control architectures explicitly take into account the need to acquire and exploit past experiences. It paves the way for machines to have reasoning abilities which is analogous to human. The research field of cognitive robotics is interdisciplinary, and uses knowledge and methods from many areas such as psychology, biology, signal processing, physics, information theory, mathematics, and statistics. The development of cognitive robotics will keep cross-fertilizing these research areas.This journal aim to collect the state-of-the-art contributions on the Computational Neuroscience, Computational Cognition and Perception, Computer Vision, Natural Language Processing, Human Action Analysis, and related applications in robotics.Editorial Board
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies. Note that the journal does not publish clinical and medical papers. We also do not publish pure machine learning papers, e.g. studies proposing variants of classifiers or pure algorithmic improvements that bear no connection to cognitive systems research in the sense above.Additionally, Cognitive Systems Research plays a special role in fostering and promoting the 'BICA Challenge' to create a real-life computational equivalent of the human mind by devoting two special issues to BICA AI (Brain-Inspired Cognitive Architectures for Artificial Intelligence) related topics each year.
The central focus of this journal is the computer analysis of pictorial information. Computer Vision and Image Understanding publishes papers covering all aspects of image analysis from the low-level, iconic processes of early vision to the high-level, symbolic processes of recognition and interpretation. A wide range of topics in the image understanding area is covered, including papers offering insights that differ from predominant views.Research Areas Include:• Theory • Early vision • Data structures and representations • Shape • Range • Motion • Matching and recognition • Architecture and languages • Vision systemsBenefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center