Aims and scope
The journal is specially intended to support the development of new computational and cognitive paradigms stemming from the cross-fertilization of various research fields. These fields include, but are not limited to, programming (logic, constraint, functional, object-oriented), distributed/parallel computing, knowledge-based systems, agent-oriented systems, and cognitive aspects of human embodied knowledge. It also encourages theoretical and/or practical papers concerning all types of learning, knowledge discovery, evolutionary mechanisms, human cognition and learning, and emergent systems that can lead to key technologies enabling us to build more complex and intelligent systems. The editorial board hopes that New Generation Computing will work as a catalyst among active researchers with broad interests by ensuring a smooth publication process.
Areas
Learning: Foundations and Models of Learning, Computational Learning Theory, Grammatical Inference, Inductive Logic Programming, Statistical Learning Methods, Bayesian Networks, Reinforcement Learning
Data Mining: Fundamental Data Mining Methods (e.g. Frequent Pattern Mining, Stream Data Mining, Graph and Network Mining, Relational Data Mining), Text and Web Mining, Statistical Methods for Data Mining, Machine Learning Methods for Data Mining, Visualization Methods for Data Mining, Practical Applications of Data Mining, Data Mining across Cyberspace and Real Space, Ethics of Data Mining (e.g. Bias, Fairness, Privacy, Social Acceptability), Data Mining to Solve Social Issues (e.g. Climate Change, Declining Birthrate and Aging Population, Cyber Warfare)
Cognitive Computing: Modeling Human Knowledge, Modeling Human Problem Solving and Learning, Semantic Computing, Modeling and Analyzing Decision Making, Cognitive Architecture, Artificial General Intelligence, Human Level AI.
Programming and Semantics: Foundations and Models of Computation, Computational Logic, Programming Systems, Declarative Programming, Concurrency and Parallelism, Quantum Computing.
Control Theory of Bio- and Nano-systems: Formal Models of Molecular Systems, Computation by Token-based Systems, Non-Boolean Representations of Signals in Nature, Cellular Automata Based on Mechanisms Found in Nature.
Bio/Nano/Molecular Computing and Engineering: Molecular Robotics & Artificial Cells, DNA Nanoengineering, Molecular Computing/Programming, Self-organizing Systems.
Skill Science and Philosophy: Skills and Knowledge in Life, Communication and Social Skills, Learning of Embodied Skills and Knowledge, “Kansei" and Value Creation, Sports Science, Measurement and Analysis of Body Movements, Systems Theory of Body, Cognitive Approach of Skill Science, Subjective Verbalization of Proprioceptive Sense, Co-evolution of Body and Language, Symbol Grounding, Symbol Generation
Computational Social Science: Social Media, Web Services, Web Mining, Social Studies, Semantic Web, Crowdsourcing, Social Systems, Social Simulation, Virtual Lab
AI to Fight COVID-19 and Other Pandemics: Infectious Disease Forecasting including Effects of Confinements and Vaccination, AI for Increasing Epidemic Preparedness in Public Health, for the Detection of Diseases and in Genome Sequencing, Role of AI in Contact Tracing, AI-Assisted Testing, Generating Recommendations for Individuals' Health, Situation Awareness, Sentiment Analysis and Trustworthiness of Information during Epidemics