Journal Guide

Artificial Cells, Nanomedicine and Biotechnology covers the frontiers of interdisciplinary research and application, combining artificial cells, nanotechnology, nanobiotechnology, biotechnology, molecular biology, bioencapsulation, novel carriers, stem cells and tissue engineering. Emphasis is on basic research, applied research, and clinical and industrial applications of the following topics:.

Artificial Intelligence, which commenced publication in 1970, is now the generally accepted premier international forum for the publication of results of current research in this field. The journal welcomes foundational and applied papers describing mature work involving computational accounts of aspects of intelligence. Specifically, it welcomes papers on:Artificial Intelligence and PhilosophyAutomated reasoning and inferenceCase-based reasoningCognitive aspects of AICommonsense reasoningConstraint processingHeuristic searchHigh-level computer visionIntelligent interfacesIntelligent roboticsKnowledge representationMachine learningMultiagent systemsNatural language processingPlanning and theories of actionReasoning under uncertainty or imprecisionThe journal reports results achieved; proposals for new ways of looking at AI problems must include demonstrations of effectiveness. Papers describing systems or architectures integrating multiple technologies are welcomed. Artificial Intelligence (AIJ) also invites papers on applications, which should describe a principled solution, emphasize its novelty, and present an in-depth evaluation of the AI techniques being exploited. The journal publishes an annual issue devoted to survey articles and also hosts a "competition section" devoted to reporting results from AI competitions. From time to time, there are special issues devoted to a particular topic; such special issues always have open calls.Artificial Intelligence caters to a broad readership. Papers that are heavily mathematical in content are welcome but should be preceded by a less technical introductory section that is accessible to a wide audience. Papers that are only mathematics, without demonstrated applicability to Artificial Intelligence problems may be returned.Benefits to authorsWe 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 pages: http://support.elsevier.com

Artificial Intelligence Review publishes state-of-the-art research reports and critical evaluations of applications, techniques and algorithms in artificial intelligence, cognitive science and related disciplines. It serves as a forum for the work of researchers and application developers from these fields. Artificial Intelligence Review also presents refereed survey and tutorial articles, as well as reviews and commentary on significant developments.

Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law.Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making: judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems: statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, andpublic administration. Intelligent processing of legal documents: conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute , resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.

Artificial Intelligence for the Earth Systems (AIES) (ISSN: 2769-7525) publishes research on the development and application of methods in Artificial Intelligence (AI), Machine Learning (ML), data science, and statistics that is relevant to meteorology, atmospheric science, hydrology, climate science, and ocean sciences. Topics include development of AI/ML, statistical, and hybrid methods and their application; development and application of methods to further the physical understanding of earth system processes from AI/ML models such as explainable and physics-based AI; the use of AI/ML to emulate components of numerical weather and climate models; incorporation of AI/ML into observation and remote sensing platforms; the use of AI/ML for data assimilation and uncertainty quantification; and societal applications of AI/ML for AIES disciplines, including ethical and responsible use of AI/ML and educational research on AI/ML.