中文簡介

本雜志旨在支持各種研究領(lǐng)域交叉施肥產(chǎn)生的新的計算和認知范式的發(fā)展。這些領(lǐng)域包括但不限于編程（邏輯、約束、功能、面向?qū)ο螅⒎植际?并行計算、基于知識的系統(tǒng)、面向代理的系統(tǒng)以及人類具體知識的認知方面。它還鼓勵有關(guān)所有類型的學習、知識發(fā)現(xiàn)、進化機制、人類認知和學習的理論和/或?qū)嵺`論文，以及能夠引導(dǎo)我們構(gòu)建更復(fù)雜和智能系統(tǒng)的關(guān)鍵技術(shù)的新興系統(tǒng)。編委會希望新一代的計算技術(shù)能夠通過確保出版過程的順利進行，在具有廣泛興趣的活躍研究人員中起到催化劑的作用。新一代計算涉及的領(lǐng)域包括：學習：學習的基礎(chǔ)和模型，計算學習理論，語法推理，歸納邏輯編程，統(tǒng)計學習方法，貝葉斯網(wǎng)絡(luò)，強化學習數(shù)據(jù)挖掘：頻繁模式挖掘、流數(shù)據(jù)挖掘、圖形和網(wǎng)絡(luò)挖掘、關(guān)系數(shù)據(jù)挖掘、文本和Web挖掘、數(shù)據(jù)挖掘的統(tǒng)計方法、數(shù)據(jù)挖掘的機器學習方法、數(shù)據(jù)挖掘的可視化方法。認知計算：建模人類知識、建模人類問題解決與學習、語義計算、建模與分析決策、認知架構(gòu)、人工通用智能、人級人工智能。編程和語義：計算的基礎(chǔ)和模型，計算邏輯，編程系統(tǒng)，聲明式編程，并發(fā)和并行，量子計算。生物和納米系統(tǒng)的控制理論：分子系統(tǒng)的形式模型，基于令牌系統(tǒng)的計算，自然界中信號的非布爾表示，基于自然界中發(fā)現(xiàn)的機制的細胞自動機。生物/納米/分子計算與工程：分子機器人與人工細胞、DNA納米工程、分子計算/編程、自組織系統(tǒng)。技能科學與哲學：生活中的技能與知識、交流與社會技能、身技能與知識的學習、“感性”與價值創(chuàng)造、體育科學、身體運動的測量與分析、身體系統(tǒng)論、技能科學的認知方法、本體感覺的主觀言語化、共同進化身體和語言的n，符號接地，符號生成計算社會科學：社會媒體、網(wǎng)絡(luò)服務(wù)、網(wǎng)絡(luò)挖掘、社會研究、語義網(wǎng)絡(luò)、眾包、社會系統(tǒng)、社會模擬、虛擬實驗室

投稿網(wǎng)址：http://www.ohmsha.co.jp/ngc/instruction.htm

英文簡介

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 covered in New Generation Computing include:Learning: Foundations and Models of Learning, Computational Learning Theory, Grammatical Inference, Inductive Logic Programming, Statistical Learning Methods, Bayesian Networks, Reinforcement LearningData Mining: 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 MiningCognitive 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 GenerationComputational Social Science: Social Media, Web Services, Web Mining, Social Studies, Semantic Web, Crowdsourcing, Social Systems, Social Simulation, Virtual Lab