Cognitive Systems Research

认知系统研究致力于人类智力水平的研究。因此，它欢迎促进自然和人工认知和智能系统的理解、设计和应用的论文。该杂志汇集了一个广泛的社区研究认知结构在体内和硅。它旨在从不同学科和认知架构的不同视角(包括生物启发和非生物启发)，以及认知系统的开发和应用，整合思想、概念、结构、理论、模型和技术。认知系统研究在培育和促进“BICA挑战”方面发挥着特殊的作用。BICA的挑战是通过每年为BICA相关主题提供两个专题，创建一个现实生活中与人类思维等价的计算模型。认知系统研究欢迎在以下范围内以原稿、短交流、调查文章等形式开展成熟前沿的研究:认知科学:包括自主认知与元认知、意象、感觉制造、元学习、自我调节学习、终身学习与认知成长、学习者的“临界量”、自然与人工创造力、情感与情感、情感能力、社会认知、自我、类人情景记忆、语言感知、加工、生产、习得与发展。实验心理学:如果以计算模型研究作为补充，将考虑对上述主题的实证研究。计算机科学与人工智能:包括认知架构、虚拟与物理认知机器人、合成字符、引导与类人学习、人机界面、视觉与计算语言学。神经科学和神经工程:包括系统级计算神经科学,认知神经科学,模型的语义和情景记忆的神经基质和意识,机构,情绪和情感,心理理论和社会认知、语言、图像、自愿控制,目标和价值体系,空间认知和实施新电脑基质如神经工程。

Cognitive Systems Research is dedicated to the study of human-level intelligence. 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 cognitive architectures in vivo and in silico. It aims to integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on cognitive architectures - both biologically-inspired and non-biologically-inspired - and the development and application of cognitive systems. 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 related topics each year.Cognitive Systems Research welcomes mature and cutting-edge research in the form of original manuscripts, short communications and survey articles within the following scope: Cognitive science: including autonomous cognition and metacognition, imagery, sensemaking, meta-learning, self-regulated learning, life-long learning and cognitive growth, "critical mass" of a learner, natural and artificial creativity, affects, emotions and feelings, emotional competence, social cognition, the self, human-like episodic memory, language perception, processing, production, acquisition and development. Experimental psychology: Empirical studies on the topics listed above will be considered if they are supplemented by computational modelling studies. Computer science and artificial intelligence: including cognitive architectures, virtual and physical cognitive robotics, synthetic characters, bootstrapped and human-like learning, human-computer interface, vision and computational linguistics. Neuroscience and neuromorphic engineering: including system-level computational neuroscience, cognitive neuroscience, models of the neural substrates of semantic and episodic memory and awareness, agency, emotions and feelings, theory of mind and social cognition, language, imagery, voluntary control, goal and value systems, spatial cognition and the implementation of new computer substrates such as neuromorphic engineering.