{"results":[{"id":"ss_54ed4248e5175767ac18556e63a099e5120a5936","title":"Ieee Transactions On Cybernetics","authors":[{"name":"Matthew Stewart"}],"abstract":"","source":"Semantic Scholar","year":2015,"language":"en","subjects":["Engineering"],"doi":"10.1016/j.wem.2014.12.006","url":"https://www.semanticscholar.org/paper/54ed4248e5175767ac18556e63a099e5120a5936","pdf_url":"http://www.wemjournal.org/article/S1080603214004256/pdf","is_open_access":true,"citations":1050,"published_at":"","score":89},{"id":"ss_979079ff368b2a32ce7546319c7837ef1793bf9b","title":"An Introduction to Cybernetics","authors":[{"name":"John von Neumann"},{"name":"C. Shannon"},{"name":"W. Mcculloch"}],"abstract":"","source":"Semantic Scholar","year":1957,"language":"en","subjects":["Philosophy"],"doi":"10.2307/3610171","url":"https://www.semanticscholar.org/paper/979079ff368b2a32ce7546319c7837ef1793bf9b","pdf_url":"http://dspace.utalca.cl/bitstream/1950/6344/2/IntroCyb.pdf","is_open_access":true,"citations":3756,"published_at":"","score":80},{"id":"ss_f936e102352d4ce5b32926f192fc660ff9af1e3f","title":"An introduction to cybernetics.","authors":[{"name":"W. R. Ashby"}],"abstract":"","source":"Semantic Scholar","year":1956,"language":"en","subjects":["Biology","Sociology"],"doi":"10.5962/bhl.title.5851","url":"https://www.semanticscholar.org/paper/f936e102352d4ce5b32926f192fc660ff9af1e3f","pdf_url":"https://www.biodiversitylibrary.org/itempdf/26977","is_open_access":true,"citations":3783,"published_at":"","score":80},{"id":"ss_38cb7889b8fa72d5ec7e7acdaa6aad4c2e6c1d0a","title":"Cybernetics, or Control and Communication in the Animal and the Machine.","authors":[{"name":"F. H. Adler"}],"abstract":"","source":"Semantic Scholar","year":1949,"language":"en","subjects":["Medicine"],"doi":"10.1001/ARCHOPHT.1949.00900040671019","url":"https://www.semanticscholar.org/paper/38cb7889b8fa72d5ec7e7acdaa6aad4c2e6c1d0a","is_open_access":true,"citations":3509,"published_at":"","score":80},{"id":"ss_6bf6d6be89580844310d7247f845afbafe6b3ac7","title":"How We Became Posthuman: Virtual Bodies in Cybernetics, Literature and Informatics by N. Katherine Hayles (review)","authors":[{"name":"J. Tambling"}],"abstract":"From the Publisher: In this age of DNA computers and artificial intelligence, information is becoming disembodied even as the \"bodies\" that once carried it vanish into virtuality. While some marvel at these changes, envisioning consciousness downloaded into a computer or humans \"beamed\" Star Trek-style, others view them with horror, seeing monsters brooding in the machines. In How We Became Posthuman, N. Katherine Hayles separates hype from fact, investigating the fate of embodiment in an information age. Hayles relates three interwoven stories: how information lost its body, that is, how it came to be conceptualized as an entity separate from the material forms that carry it; the cultural and technological construction of the cyborg; and the dismantling of the liberal humanist \"subject\" in cybernetic discourse, along with the emergence of the \"posthuman.\" Ranging widely across the history of technology, cultural studies, and literary criticism, Hayles shows what had to be erased, forgotten, and elided to conceive of information as a disembodied entity. Thus she moves from the post-World War II Macy Conferences on cybernetics to the 1952 novel Limbo by cybernetics aficionado Bernard Wolfe; from the concept of self-making to Philip K. Dick's literary explorations of hallucination and reality; and from artificial life to postmodern novels exploring the implications of seeing humans as cybernetic systems. Although becoming posthuman can be nightmarish, Hayles shows how it can also be liberating. From the birth of cybernetics to artificial life, How We Became Posthuman provides an indispensable account of how we arrived in our virtual age, and of where we might go from here.","source":"Semantic Scholar","year":2001,"language":"en","subjects":["Sociology","Art"],"doi":"10.2307/3735725","url":"https://www.semanticscholar.org/paper/6bf6d6be89580844310d7247f845afbafe6b3ac7","is_open_access":true,"citations":1658,"published_at":"","score":80},{"id":"doaj_10.60797/COMP.2026.9.1","title":"РОЛЬ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В АВТОМАТИЗАЦИИ НАУЧНЫХ ИССЛЕДОВАНИЙ: ОТ АНАЛИЗА ЛИТЕРАТУРЫ ДО ГЕНЕРАЦИИ ГИПОТЕЗ","authors":[{"name":"Анастас К.В."}],"abstract":"Современная научная деятельность характеризуется экспоненциальным ростом объема публикаций и данных, что создает значительные трудности в систематизации, анализе и интерпретации информации. В этих условиях технологии искусственного интеллекта (ИИ) становятся ключевым инструментом автоматизации процессов научного исследования. В статье рассматриваются современные подходы к применению методов машинного обучения, глубоких нейронных сетей и обработки естественного языка (NLP) для анализа научной литературы, выявления скрытых закономерностей, генерации гипотез и планирования экспериментальной работы. Особое внимание уделено практическим примерам применения ИИ в биоинформатике, химии, медицине, физике и компьютерных науках, а также анализу ограничений, связанных с интерпретируемостью моделей, надежностью выводов и соблюдением этических норм. Обсуждаются перспективы развития гибридных систем, обеспечивающих совместную работу человека и ИИ, и возможности повышения аналитических компетенций исследователей в условиях цифровизации науки.","source":"DOAJ","year":2026,"language":"","subjects":["Electronic computers. Computer science","Cybernetics"],"doi":"10.60797/COMP.2026.9.1","url":"https://informatics.cifra.science/archive/1-9-2026-january/10.60797/COMP.2026.9.1","is_open_access":true,"published_at":"","score":70},{"id":"arxiv_2506.07971","title":"CyberV: Cybernetics for Test-time Scaling in Video Understanding","authors":[{"name":"Jiahao Meng"},{"name":"Shuyang Sun"},{"name":"Yue Tan"},{"name":"Lu Qi"},{"name":"Yunhai Tong"},{"name":"Xiangtai Li"},{"name":"Longyin Wen"}],"abstract":"Current Multimodal Large Language Models (MLLMs) may struggle with understanding long or complex videos due to computational demands at test time, lack of robustness, and limited accuracy, primarily stemming from their feed-forward processing nature. These limitations could be more severe for models with fewer parameters. To address these limitations, we propose a novel framework inspired by cybernetic principles, redesigning video MLLMs as adaptive systems capable of self-monitoring, self-correction, and dynamic resource allocation during inference. Our approach, CyberV, introduces a cybernetic loop consisting of an MLLM Inference System, a Sensor, and a Controller. Specifically, the sensor monitors forward processes of the MLLM and collects intermediate interpretations, such as attention drift, then the controller determines when and how to trigger self-correction and generate feedback to guide the next round. This test-time adaptive scaling framework enhances frozen MLLMs without requiring retraining or additional components. Experiments demonstrate significant improvements: CyberV boosts Qwen2.5-VL-7B by 8.3% and InternVL3-8B by 5.5% on VideoMMMU, surpassing the competitive proprietary model GPT-4o. When applied to Qwen2.5-VL-72B, it yields a 10.0% improvement, achieving performance even comparable to human experts. Furthermore, our method demonstrates consistent gains on general-purpose benchmarks, such as VideoMME and WorldSense, highlighting its effectiveness and generalization capabilities in making MLLMs more robust and accurate for dynamic video understanding. The code is released at https://github.com/marinero4972/CyberV.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CV"],"url":"https://arxiv.org/abs/2506.07971","pdf_url":"https://arxiv.org/pdf/2506.07971","is_open_access":true,"published_at":"2025-06-09T17:45:18Z","score":69},{"id":"crossref_10.5117/9789089646682_pt01_ch02","title":"Cybernetics","authors":[{"name":"Ute Holl"}],"abstract":"","source":"CrossRef","year":2025,"language":"en","subjects":null,"doi":"10.5117/9789089646682_pt01_ch02","url":"https://doi.org/10.5117/9789089646682_pt01_ch02","is_open_access":true,"published_at":"","score":69},{"id":"ss_863e0583a6f26bbd811724045323386661446e04","title":"Cybernetics","authors":[{"name":"E. Glasersfeld"}],"abstract":"","source":"Semantic Scholar","year":2018,"language":"en","subjects":null,"doi":"10.1201/9781482277180-1","url":"https://www.semanticscholar.org/paper/863e0583a6f26bbd811724045323386661446e04","is_open_access":true,"citations":213,"published_at":"","score":68.39},{"id":"ss_81b1007337801af8541d04675c0e8db6d9465a40","title":"Bibliometric mapping in the landscape of cybernetics: insights into global research networks","authors":[{"name":"I. Nica"}],"abstract":"PurposeThis bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.Design/methodology/approachThe analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.FindingsThe results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.Originality/valueThis study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Computer Science"],"doi":"10.1108/k-11-2023-2365","url":"https://www.semanticscholar.org/paper/81b1007337801af8541d04675c0e8db6d9465a40","is_open_access":true,"citations":9,"published_at":"","score":68.27000000000001},{"id":"doaj_IMPRESSIONS+OF+THE+PARTICIPANT+OF+THE+TECHNOLOGICAL+CONFERENCE+%22CIPR-2024%22","title":"IMPRESSIONS OF THE PARTICIPANT OF THE TECHNOLOGICAL CONFERENCE \"CIPR-2024\"","authors":[{"name":"Elena G. Panarskaya"}],"abstract":"","source":"DOAJ","year":2024,"language":"","subjects":["Information technology","Information theory"],"url":"https://bit.spels.ru/index.php/bit/article/view/1651","is_open_access":true,"published_at":"","score":68},{"id":"doaj_IMPRESSIONS+OF+THE+PARTICIPANTS+OF+THE+X+INTERNATIONAL+MILITARY-TECHNICAL+FORUM+%22ARMY-2024%22","title":"IMPRESSIONS OF THE PARTICIPANTS OF THE X INTERNATIONAL MILITARY-TECHNICAL FORUM \"ARMY-2024\"","authors":[{"name":"Alexander Yu. Nikiforov"},{"name":"Nikolai A. Usachev"},{"name":"Alexander V. Ermakov"}],"abstract":"","source":"DOAJ","year":2024,"language":"","subjects":["Information technology","Information theory"],"url":"https://bit.spels.ru/index.php/bit/article/view/1686","is_open_access":true,"published_at":"","score":68},{"id":"arxiv_2409.16314","title":"Definition of Cybernetical Neuroscience","authors":[{"name":"Alexander Fradkov"}],"abstract":"A new scientific field is introduced and discussed, named cybernetical neuroscience, which studies mathematical models adopted in computational neuroscience by methods of cybernetics -- the science of control and communication in a living organism, machine and society. It also considers the practical application of the results obtained when studying mathematical models. The main tasks and methods, as well as some results of cybernetic neuroscience are considered.","source":"arXiv","year":2024,"language":"en","subjects":["q-bio.NC","math.OC"],"url":"https://arxiv.org/abs/2409.16314","pdf_url":"https://arxiv.org/pdf/2409.16314","is_open_access":true,"published_at":"2024-09-14T13:35:59Z","score":68},{"id":"arxiv_2404.02688","title":"Reinforcement Learning in Categorical Cybernetics","authors":[{"name":"Jules Hedges"},{"name":"Riu Rodríguez Sakamoto"}],"abstract":"We show that several major algorithms of reinforcement learning (RL) fit into the framework of categorical cybernetics, that is to say, parametrised bidirectional processes. We build on our previous work in which we show that value iteration can be represented by precomposition with a certain optic. The outline of the main construction in this paper is: (1) We extend the Bellman operators to parametrised optics that apply to action-value functions and depend on a sample. (2) We apply a representable contravariant functor, obtaining a parametrised function that applies the Bellman iteration. (3) This parametrised function becomes the backward pass of another parametrised optic that represents the model, which interacts with an environment via an agent. Thus, parametrised optics appear in two different ways in our construction, with one becoming part of the other. As we show, many of the major classes of algorithms in RL can be seen as different extremal cases of this general setup: dynamic programming, Monte Carlo methods, temporal difference learning, and deep RL. We see this as strong evidence that this approach is a natural one and believe that it will be a fruitful way to think about RL in the future.","source":"arXiv","year":2024,"language":"en","subjects":["cs.LG","math.CT"],"doi":"10.4204/EPTCS.429.15","url":"https://arxiv.org/abs/2404.02688","pdf_url":"https://arxiv.org/pdf/2404.02688","is_open_access":true,"published_at":"2024-04-03T12:36:25Z","score":68},{"id":"arxiv_2403.04292","title":"A challenge in A(G)I, cybernetics revived in the Ouroboros Model as one algorithm for all thinking","authors":[{"name":"Knud Thomsen"}],"abstract":"A topical challenge for algorithms in general and for automatic image categorization and generation in particular is presented in the form of a drawing for AI to understand. In a second vein, AI is challenged to produce something similar from verbal description. The aim of the paper is to highlight strengths and deficiencies of current Artificial Intelligence approaches while coarsely sketching a way forward. A general lack of encompassing symbol-embedding and (not only) -grounding in some bodily basis is made responsible for current deficiencies. A concomitant dearth of hierarchical organization of concepts follows suite. As a remedy for these shortcomings, it is proposed to take a wide step back and to newly incorporate aspects of cybernetics and analog control processes. It is claimed that a promising overarching perspective is provided by the Ouroboros Model with a valid and versatile algorithmic backbone for general cognition at all accessible levels of abstraction and capabilities. Reality, rules, truth, and Free Will are all useful abstractions according to the Ouroboros Model. Logic deduction as well as intuitive guesses are claimed as produced on the basis of one compartmentalized memory for schemata and a pattern-matching, i.e., monitoring process termed consumption analysis. The latter directs attention on short (attention proper) and also on long times scales (emotional biases). In this cybernetic approach, discrepancies between expectations and actual activations (e.g., sensory precepts) drive the general process of cognition and at the same time steer the storage of new and adapted memory entries. Dedicated structures in the human brain work in concert according to this scheme.","source":"arXiv","year":2024,"language":"en","subjects":["cs.AI"],"doi":"10.55092/aias20240001","url":"https://arxiv.org/abs/2403.04292","pdf_url":"https://arxiv.org/pdf/2403.04292","is_open_access":true,"published_at":"2024-03-07T07:39:54Z","score":68},{"id":"ss_638dff8a54ffba709bb3aefc3a84f06f4587d419","title":"Mapping the Evolution of Cybernetics: A Bibliometric Perspective","authors":[{"name":"Bianca Cibu"},{"name":"Camelia Delcea"},{"name":"Adrian Domenteanu"},{"name":"Gabriel Dumitrescu"}],"abstract":"In this study, we undertake a comprehensive bibliometric analysis of the cybernetics research field. We compile a dataset of 4856 papers from the ISI Web of Science database spanning 1975–2022, employing keywords related to cybernetics. Our findings reveal an annual growth rate of 7.56% in cybernetics research over this period, indicating sustained scholarly interest. By examining the annual progression of scientific production, we have identified three distinct periods characterized by significant disruptions in yearly publication trends. These disruptions have been thoroughly investigated within the paper, utilizing a longitudinal analysis of thematic evolution. We also identify emerging research trends through keyword analysis. Furthermore, we investigate collaborative networks among authors, their institutional affiliations, and global representation to elucidate the dissemination of cybernetics research. Employing n-gram analysis, we uncover diverse applications of cybernetics in fields such as computer science, information science, social sciences, sustainable development, supply chain, knowledge management, system dynamics, and medicine. The study contributes to enhancing the understanding of the evolving cybernetics landscape. Moreover, the conducted analysis underscores the versatile applicability across various academic and practical domains associated with the cybernetics field.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Computer Science"],"doi":"10.3390/computers12110237","url":"https://www.semanticscholar.org/paper/638dff8a54ffba709bb3aefc3a84f06f4587d419","pdf_url":"https://www.mdpi.com/2073-431X/12/11/237/pdf?version=1700120703","is_open_access":true,"citations":29,"published_at":"","score":67.87},{"id":"ss_6aa1bd60e4df6693195476edeb9ea1b8a2a33b53","title":"A Brief Review of Systems, Cybernetics, and Complexity","authors":[{"name":"J. Alvarez"},{"name":"P. Ramírez-Correa"}],"abstract":"We believe that the ongoing global pandemic has highlighted the need for comprehensive approaches to address issues that transcend geographical and cultural boundaries. Therefore, this article aims to provide a general but abstract review to allow readers of a broad spectrum to learn the basic principles of three related concepts: systems, cybernetics, and complexity. Additionally, to better exemplify these concepts, we offer a review of works from the last decade that use systems theory, complexity, and cybernetics for their development. In this context, the result of this review will allow for breaking down the barriers of reductionist silos of knowledge and fostering a multidisciplinary and interdisciplinary dialogue.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Computer Science"],"doi":"10.1155/2023/8205320","url":"https://www.semanticscholar.org/paper/6aa1bd60e4df6693195476edeb9ea1b8a2a33b53","pdf_url":"https://downloads.hindawi.com/journals/complexity/2023/8205320.pdf","is_open_access":true,"citations":17,"published_at":"","score":67.50999999999999},{"id":"ss_687c726babe289e506c951e19782a968f7bed740","title":"From Molecular Robotics to Molecular Cybernetics: The First Step Toward Chemical Artificial Intelligence","authors":[{"name":"A. Kuzuya"},{"name":"S. Nomura"},{"name":"T. Toyota"},{"name":"T. Nakakuki"},{"name":"S. Murata"}],"abstract":"“Molecular Cybernetics” is an emerging research field aiming the development of “Chemical AI”, artificial intelligence with memory and learning capabilities based on molecular communication. It is originated from “Molecular Robotics,” which studies molecular systems that comprise of the three basic elements of robots; Sensing, Planning, and Acting. Development of an Amoeba-type molecular robot (unicellular artificial cell,) motivated the construction of multicellular artificial cell systems mimicking nerve systems. The major challenges in molecular cybernetics are molecular communication over two lipid-bilayer compartments, amplification of molecular information in a compartment, and large deformation of the compartment triggered by molecular signal, etc. Recently reported molecular devices and systems that contributes to the realization of Chemical AI are overviewed.","source":"Semantic Scholar","year":2023,"language":"en","subjects":["Computer Science"],"doi":"10.1109/TMBMC.2023.3304243","url":"https://www.semanticscholar.org/paper/687c726babe289e506c951e19782a968f7bed740","pdf_url":"https://ieeexplore.ieee.org/ielx7/6687308/7181695/10214301.pdf","is_open_access":true,"citations":15,"published_at":"","score":67.45},{"id":"ss_9088b5478fc706f368d2d1fd5661aba9384d782b","title":"Endocrine cybernetics: neuropeptides as molecular switches in behavioural decisions","authors":[{"name":"D. Nässel"},{"name":"Meet Zandawala"}],"abstract":"Plasticity in animal behaviour relies on the ability to integrate external and internal cues from the changing environment and hence modulate activity in synaptic circuits of the brain. This context-dependent neuromodulation is largely based on non-synaptic signalling with neuropeptides. Here, we describe select peptidergic systems in the Drosophila brain that act at different levels of a hierarchy to modulate behaviour and associated physiology. These systems modulate circuits in brain regions, such as the central complex and the mushroom bodies, which supervise specific behaviours. At the top level of the hierarchy there are small numbers of large peptidergic neurons that arborize widely in multiple areas of the brain to orchestrate or modulate global activity in a state and context-dependent manner. At the bottom level local peptidergic neurons provide executive neuromodulation of sensory gain and intrinsically in restricted parts of specific neuronal circuits. The orchestrating neurons receive interoceptive signals that mediate energy and sleep homeostasis, metabolic state and circadian timing, as well as external cues that affect food search, aggression or mating. Some of these cues can be triggers of conflicting behaviours such as mating versus aggression, or sleep versus feeding, and peptidergic neurons participate in circuits, enabling behaviour choices and switches.","source":"Semantic Scholar","year":2022,"language":"en","subjects":["Medicine"],"doi":"10.1098/rsob.220174","url":"https://www.semanticscholar.org/paper/9088b5478fc706f368d2d1fd5661aba9384d782b","pdf_url":"https://doi.org/10.1098/rsob.220174","is_open_access":true,"citations":46,"published_at":"","score":67.38},{"id":"ss_92508b464e09dbc0ae75c22e9aec9f5cd17b0033","title":"IEEE SYSTEMS, MAN, AND CYBERNETICS SOCIETY","authors":null,"abstract":"","source":"Semantic Scholar","year":2023,"language":"en","subjects":null,"doi":"10.1109/tcyb.2022.3232903","url":"https://www.semanticscholar.org/paper/92508b464e09dbc0ae75c22e9aec9f5cd17b0033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6221036/10016773/10016899.pdf","is_open_access":true,"citations":10,"published_at":"","score":67.3}],"total":134466,"page":1,"page_size":20,"sources":["DOAJ","arXiv","Semantic Scholar","CrossRef"],"query":"Cybernetics"}