Viacheslav Wolfengagen , Larisa Ismailova , Sergey Kosikov , Igor Slieptsov , Sebastian Dohrn , Alexander Marenkov , Vladislav Zaytsev
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引用次数: 0
Abstract
In the present work, efforts have been made to create a configuration-based approach to knowledge extraction. The notion of granularity is developed, which allows fine-tuning the expressive possibilities of the semantic network. As known, the central issues for knowledge-based systems are what’s-in-a-node and what’s-in-a-link. As shown, the answer can be obtained from the functor-as-object representation. Then the nodes are functors, and the main links are natural transformations. Such a model is applicable to represent morphing, and the object is considered as a process, which is in a harmony with current ideas on computing. It is possible to represent information channels that carry out the transformations of processes. The possibility of generating displaced concepts and the generation of families of their morphs is shown, the evolvent of stages of knowledge and properties of the process serve as parameters.
期刊介绍：
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.
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