Готові списки джерел за темами / Cognitive computation

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  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій
  6. Звіти організацій

Добірка наукової літератури з теми "Cognitive computation"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 31 липня 2025

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Статті в журналах з теми "Cognitive computation"

1

Bishop, John Mark. "A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism." Cognitive Computation 1, no. 3 (2009): 221–33. http://dx.doi.org/10.1007/s12559-009-9019-6.

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Magnani, Lorenzo. "Disseminated Computation, Cognitive Domestication of New Ignorant Substrates, and Overcomputationalization." Proceedings 47, no. 1 (2020): 29. http://dx.doi.org/10.3390/proceedings2020047029.

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Анотація:
Eco-cognitive computationalism considers computation in the context of following some of the main tenets advanced by the recent cognitive science views on embodied, situated and distributed cognition. It is in the framework of this eco-cognitive perspective that we can usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities by the morphological features: ignorant bodies can be domesticated to become useful “mimetic bodies”, that is to be able to render an intertwined computation simpler, r
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3

Magnani, Lorenzo. "Disseminated Computation, Cognitive Domestication of New Ignorant Substrates, and Overcomputationalization." Proceedings 47, no. 1 (2020): 29. http://dx.doi.org/10.3390/proceedings47010029.

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Анотація:
Eco-cognitive computationalism considers computation in the context of following some of the main tenets advanced by the recent cognitive science views on embodied, situated and distributed cognition. It is in the framework of this eco-cognitive perspective that we can usefully analyze the recent attention in computer science devoted to the importance of the simplification of cognitive and motor tasks caused in organic entities by the morphological features: ignorant bodies can be domesticated to become useful “mimetic bodies”, that is to be able to render an intertwined computation simpler, r
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4

Magnani, Lorenzo. "Eccentric Computational Embodiments: Cognitive Domestication of External Entities." Proceedings 47, no. 1 (2020): 36. http://dx.doi.org/10.3390/proceedings2020047036.

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Анотація:
Eco-cognitive computationalism sees computation in context, adopting the intellectual visions advanced by the cognitive science perspectives on embodied, situated, and distributed cognition. It is in this framework that we can fruitfully study the relevance in recent computer science devoted to the simplification of cognitive and motor tasks generated in organic entities by the morphological aspects. Ignorant bodies can be cognitively “domesticated” to become useful “mimetic bodies'', which originate eccentric new computational embodiments capable of rendering an involved computation simpler a
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Magnani, Lorenzo. "Eccentric Computational Embodiments: Cognitive Domestication of External Entities." Proceedings 47, no. 1 (2020): 36. http://dx.doi.org/10.3390/proceedings47010036.

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Анотація:
Eco-cognitive computationalism sees computation in context, adopting the intellectual visions advanced by the cognitive science perspectives on embodied, situated, and distributed cognition. It is in this framework that we can fruitfully study the relevance in recent computer science devoted to the simplification of cognitive and motor tasks generated in organic entities by the morphological aspects. Ignorant bodies can be cognitively “domesticated” to become useful “mimetic bodies'', which originate eccentric new computational embodiments capable of rendering an involved computation simpler a
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6

Faix, Marvin, Emmanuel Mazer, Raphaël Laurent, Mohamad Othman Abdallah, Ronan Le Hy, and Jorge Lobo. "Cognitive Computation." International Journal of Software Science and Computational Intelligence 9, no. 3 (2017): 37–58. http://dx.doi.org/10.4018/ijssci.2017070103.

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Анотація:
Probabilistic programming allows artificial systems to better operate with uncertainty, and stochastic arithmetic provides a way to carry out approximate computations with few resources. As such, both are plausible models for natural cognition. The authors' work on the automatic design of probabilistic machines computing soft inferences, with an arithmetic based on stochastic bitstreams, allowed to develop the following compilation toolchain: given a high-level description of some general problem, formalized as a Bayesian Program, the toolchain automatically builds a low-level description of a
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Taylor, J. G. "Cognitive Computation." Cognitive Computation 1, no. 1 (2009): 4–16. http://dx.doi.org/10.1007/s12559-008-9001-8.

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Smolensky, Paul. "Symbolic functions from neural computation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, no. 1971 (2012): 3543–69. http://dx.doi.org/10.1098/rsta.2011.0334.

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Анотація:
Is thought computation over ideas? Turing, and many cognitive scientists since, have assumed so, and formulated computational systems in which meaningful concepts are encoded by symbols which are the objects of computation. Cognition has been carved into parts, each a function defined over such symbols. This paper reports on a research program aimed at computing these symbolic functions without computing over the symbols. Symbols are encoded as patterns of numerical activation over multiple abstract neurons, each neuron simultaneously contributing to the encoding of multiple symbols. Computati
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Magnani, Lorenzo. "Conceptualizing Machines in an Eco-Cognitive Perspective." Philosophies 7, no. 5 (2022): 94. http://dx.doi.org/10.3390/philosophies7050094.

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Анотація:
Eco-cognitive computationalism explores computing in context, adhering to some of the key ideas presented by modern cognitive science perspectives on embodied, situated, and distributed cognition. First of all, when physical computation is seen from the perspective of the ecology of cognition it is possible to clearly understand the role Turing assigned to the process of “education” of the machine, paralleling it to the education of human brains, in the invention of the Logical Universal Machine. It is this Turing’s emphasis on education that furnishes the justification of the conceptualizatio
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Dodig-Crnkovic, Gordana, and Marcin Miłkowski. "Discussion on the Relationship between Computation, Information, Cognition, and Their Embodiment." Entropy 25, no. 2 (2023): 310. http://dx.doi.org/10.3390/e25020310.

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Анотація:
Three special issues of Entropy journal have been dedicated to the topics of “Information-Processing and Embodied, Embedded, Enactive Cognition”. They addressed morphological computing, cognitive agency, and the evolution of cognition. The contributions show the diversity of views present in the research community on the topic of computation and its relation to cognition. This paper is an attempt to elucidate current debates on computation that are central to cognitive science. It is written in the form of a dialog between two authors representing two opposed positions regarding the issue of w
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Дисертації з теми "Cognitive computation"

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Cattinelli, I. "INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155482.

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This Thesis describes our work at the boundary between Computer Science and Cognitive (Neuro)Science. In particular, (1) we have worked on methodological improvements to clustering-based meta-analysis of neuroimaging data, which is a technique that allows to collectively assess, in a quantitative way, activation peaks from several functional imaging studies, in order to extract the most robust results in the cognitive domain of interest. Hierarchical clustering is often used in this context, yet it is prone to the problem of non-uniqueness of the solution: a different permutation of the same i
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Mansinghka, Vikash Kumar. "Natively probabilistic computation." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47892.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.<br>Includes bibliographical references (leaves 129-135).<br>I introduce a new set of natively probabilistic computing abstractions, including probabilistic generalizations of Boolean circuits, backtracking search and pure Lisp. I show how these tools let one compactly specify probabilistic generative models, generalize and parallelize widely used sampling algorithms like rejection sampling and Markov chain Monte Carlo, and solve difficult Bayesian inference problems. I first introduce Church, a
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3

Sprevak, Mark Daniel. "Computation in mind and world : a realist account of computation in cognitive science." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613848.

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Jonas, Eric Michael. "Stochastic architectures for probabilistic computation." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87457.

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Анотація:
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 107-111).<br>The brain interprets ambiguous sensory information faster and more reliably than modern computers, using neurons that are slower and less reliable than logic gates. But Bayesian inference, which is at the heart of many models for sensory information processing and cognition, as well as many machine intelligence systems, appears computationally challenging, even given modern transistor speeds
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Ullman, Michael Thomas. "The computation of inflectional morphology." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12489.

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Ghahramani, Zoubin. "Computation and psychophysics of sensorimotor integration." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11123.

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Kell, Alexander James Eaton. "Hierarchy and invariance in auditory cortical computation." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/132746.

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Thesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, June, 2019<br>Cataloged from the PDF version of thesis. "June 2019"--Hand written on title page.<br>Includes bibliographical references.<br>With ease, we recognize a friend's voice in a crowd, or pick out the first violin in a concerto. But the effortlessness of everyday perception masks its computational challenge. Perception does not occur in the eyes and ears - indeed, nearly half of primate cortex is dedicated to it. While much is known about peripheral auditory processing, au
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Heirdsfield, Ann M. "Mental computation: The identification of associated cognitive, metacognitive and affective factors." Thesis, Queensland University of Technology, 2001. https://eprints.qut.edu.au/36637/1/36637_Digitised%20Thesis.pdf.

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Анотація:
The purpose of the study was to develop an explanation why some children are better at addition and subtraction mental computation than others. For the purposes of this thesis, mental computation was defined as "the process of carrying out arithmetic calculations without the aid of external devices" (Sowder, 1988, p.182). To reflect current views of mental computation as calculating with the head, rather than merely, in the head, the definition was extended to calculating using strategies with understanding (Anghileri, 1999). Thus, proficiency was not confined to accuracy, but also included fl
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Wells, Andrew J. "The External Tape Hypothesis : a Turing machine based approach to cognitive computation." Thesis, London School of Economics and Political Science (University of London), 1994. http://etheses.lse.ac.uk/118/.

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The symbol processing or "classical cognitivist" approach to mental computation suggests that the cognitive architecture operates rather like a digital computer. The components of the architecture are input, output and central systems. The input and output systems communicate with both the internal and external environments of the cognizer and transmit codes to and from the rule governed, central processing system which operates on structured representational expressions in the internal environment. The connectionist approach, by contrast, suggests that the cognitive architecture should be tho
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Aboalela, Rania Anwar. "An Assessment of Knowledge by Pedagogical Computation on Cognitive Level mapped Concept Graphs." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1496941747313396.

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Книги з теми "Cognitive computation"

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Wells, A. J. Rethinking Cognitive Computation. Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-1-137-06661-9.

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Sun, Fuchun, and Jianmin Li, eds. Cognitive Computation and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0885-7.

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Sun, Fuchun, Jianmin Li, Huaping Liu, and Zhongyi Chu, eds. Cognitive Computation and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2789-0.

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Xu, Bin, and Jianlong Qiu, eds. Cognitive Computation and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7438-1.

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Xu, Bin, and Jianlong Qiu, eds. Cognitive Computation and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7352-0.

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Fresco, Nir. Physical Computation and Cognitive Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-41375-9.

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Pylyshyn, Zenon W. Computation and cognition: Toward a foundation for cognitive science. MIT Press, 1989.

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Pylyshyn, Zenon W. Computation and cognition: Toward a foundation for cognitive science. 2nd ed. MIT Press, 1985.

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9

Kryzhanovsky, Boris, Witali Dunin-Barkowski, and Vladimir Redko, eds. Advances in Neural Computation, Machine Learning, and Cognitive Research. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-66604-4.

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Spain) Neural Computation and Psychology Workshop (13th 2012 San Sebastián. Computational models of cognitive processes: Proceedings of the 13th Neural Computation and Psychology Workshop, San Sebastian, Spain, 12-14 July 2012. Edited by Mayor, Julien, editor of compilation and Gomez, Pablo (Pablo Alegria), editor of compilation. World Scientific, 2014.

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Частини книг з теми "Cognitive computation"

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Smith, Aaron C. T. "Computation." In Cognitive Mechanisms of Belief Change. Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-57895-2_3.

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Wells, A. J. "Ecological Functionalism: Computation." In Rethinking Cognitive Computation. Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-1-137-06661-9_19.

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Wells, A. J. "Turing’s Analysis of Computation." In Rethinking Cognitive Computation. Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-1-137-06661-9_6.

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Schweizer, Paul. "Cognitive Computation sans Representation." In Philosophical Studies Series. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61043-6_4.

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Wang, Wenfeng, Hengjin Cai, Xiangyang Deng, Chenguang Lu, and Limin Zhang. "Cognitive Computation and Systems." In Interdisciplinary Evolution of the Machine Brain. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4244-6_2.

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Stufflebeam, Robert S. "Representation and Computation." In A Companion to Cognitive Science. Blackwell Publishing Ltd, 2017. http://dx.doi.org/10.1002/9781405164535.ch50.

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Giannopulu, Irini. "Introduction." In Cognitive Computation Trends. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95558-2_1.

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Giannopulu, Irini. "The Mind." In Cognitive Computation Trends. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95558-2_2.

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Giannopulu, Irini. "Dynamic Embrained Systems." In Cognitive Computation Trends. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95558-2_3.

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Giannopulu, Irini. "Externalised Mind 1." In Cognitive Computation Trends. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95558-2_4.

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Тези доповідей конференцій з теми "Cognitive computation"

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Maharishi, Ankita Agarwal, J. Jesupriya, Siddharth Sriram, Siba Prasada Tripathy, Abhishek Singla, and Yashoda L. "Opportunistic Spectrum Access Techniques for Cognitive Radio Networks." In 2025 International Conference on Automation and Computation (AUTOCOM). IEEE, 2025. https://doi.org/10.1109/autocom64127.2025.10957497.

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Maley, Corey. "Analog Computation in Computational Cognitive Neuroscience." In 2018 Conference on Cognitive Computational Neuroscience. Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1178-0.

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Piccinini, Gualtiero. "Non-Computational Functionalism: Computation and the Function of Consciousness." In 2018 Conference on Cognitive Computational Neuroscience. Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1022-0.

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Ciftcioglu, Ozer, and Michael S. Bittermann. "Generic cognitive computing for cognition." In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7256942.

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Fiorini, Rodolfo A. "Quantum cognitive computation by CICT." In 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2016. http://dx.doi.org/10.1109/icci-cc.2016.7862085.

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Shao, Shuangjia, Guiming Luo, Jian Luo, and Xibin Zhao. "Circuit delay computation based on ITTPN." In 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2013. http://dx.doi.org/10.1109/icci-cc.2013.6622282.

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Luo, Jian, Guiming Luo, and Yang Zhao. "Satisfiability degree computation for linear temporal logic." In Cognitive Computing (ICCI-CC). IEEE, 2011. http://dx.doi.org/10.1109/coginf.2011.6016168.

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Faix, Marvin, Emmanuel Mazer, Raphael Laurent, Mohamad Othman Abdallah, Ronan Le Hy, and Jorge Lobo. "Cognitive computation: A Bayesian machine case study." In 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2015. http://dx.doi.org/10.1109/icci-cc.2015.7259367.

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Papadimitriou, Christos H., Santosh S. Vempala, Daniel Mitropolsky, Michael J. Collins, Wolfgang Maass, and Larry F. Abbott. "A Calculus for Brain Computation." In 2019 Conference on Cognitive Computational Neuroscience. Cognitive Computational Neuroscience, 2019. http://dx.doi.org/10.32470/ccn.2019.1381-0.

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Anderson, J. A. "Cognitive computation: the Ersatz Brain project." In Fourth IEEE Conference on Cognitive Informatics, 2005. (ICCI 2005). IEEE, 2005. http://dx.doi.org/10.1109/coginf.2005.1532607.

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Звіти організацій з теми "Cognitive computation"

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Pasupuleti, Murali Krishna. Neural Computation and Learning Theory: Expressivity, Dynamics, and Biologically Inspired AI. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv425.

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Abstract: Neural computation and learning theory provide the foundational principles for understanding how artificial and biological neural networks encode, process, and learn from data. This research explores expressivity, computational dynamics, and biologically inspired AI, focusing on theoretical expressivity limits, infinite-width neural networks, recurrent and spiking neural networks, attractor models, and synaptic plasticity. The study investigates mathematical models of function approximation, kernel methods, dynamical systems, and stability properties to assess the generalization capa
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Kosslyn, Stephen M. DURIP - Computational Modeling of Cognitive Processes. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada219934.

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Faden, Alan I. Georgetown Institute for Cognitive and Computational Sciences. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada373779.

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Ledley, Robert S., and Alan I. Faden. Georgetown Institute for Cognitive and Computational Sciences. Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada289775.

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Moore, Jr, and L. R. Cognitive Model Exploration and Optimization: A New Challenge for Computational Science. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada539438.

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Just, Marcel A., Patricia A. Carpenter, Cleotilde Gonzalez, and Javier Lerch. Integrated Cognitive Computational and Biological Assessment of Workload in Decision Making. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada418079.

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Castro, Carolina Robledo, Piedad Rocio Lerma-Castaño, and Luis Gerardo Pachón-Ospina. Rehabilitation programs based on computational systems: effects in the executive functions in young and middle adulthood: A scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.10.0052.

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Review question / Objective: To identify empirical studies that measured the feasibility and effect of computer-based executive function stimulation and rehabilitation programs in the young and middle adult population. Background: Reviews that evaluate the effectiveness of computerized cognitive training programs on executive functions in different population groups have shown contradictory results, to a certain extent associated with the methodological characteristics of said studies (Gates et al., 2019; 2020); most of them These reviews have focused on older adults (Ten Brinke et al., 2020;
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Gray, Wayne D. Computational Cognitive Modeling of Adaptive Choice Behavior in a Dynamic Decision Paradigm. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada444683.

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Lu, Zhong-Lin. Workshop on Cognitive Science from Cellular Mechanisms to Computational Theories (CS-2009). Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada533451.

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Schunn, C. D. A Review of Human Spatial Representations Computational, Neuroscience, Mathematical, Developmental, and Cognitive Psychology Considerations. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada440864.

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