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Статті в журналах з теми "Cognitive computation"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 19 липня 2025

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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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2

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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5

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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7

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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8

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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9

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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10

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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11

van der Velde, Frank, and Marc de Kamps. "Toward a synthesis of dynamical systems and classical computation." Behavioral and Brain Sciences 21, no. 5 (1998): 652–53. http://dx.doi.org/10.1017/s0140525x98501732.

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Анотація:

Cognitive agents are dynamical systems but not quantitative dynamical systems. Quantitative systems are forms of analogue computation, which is physically too unreliable as a basis for cognition. Instead, cognitive agents are dynamical systems that implement discrete forms of computation. Only such a synthesis of discrete computation and dynamical systems can provide the mathematical basis for modeling cognitive behavior.

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12

Dodig-Crnkovic, Gordana. "Cognition as Morphological/Morphogenetic Embodied Computation In Vivo." Entropy 24, no. 11 (2022): 1576. http://dx.doi.org/10.3390/e24111576.

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Анотація:

Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The pre

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13

Chia, Kok Hwee, and Meng Lek Ng. "Cognition, cognitive abilities & cognitive training program." Unlimited Human! 2021, Summer (2025): 4–6. https://doi.org/10.5281/zenodo.15227209.

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Анотація:

Cognition encompasses many aspects of cognitive functions as well as processes that include attention and concentration, the concept formation of knowledge, memory, rational thinking (i.e., judgment and evaluation), reasoning and logic, computation, problem solving and choice/decision making, receptive and expressive language processing that includes different levels of comprehension as well as composition of ideas and thoughts. Cognitive processes use existing knowledge and generate new knowledge. In this paper, the two authors differentiated between abilities and skills, examined the hierarc

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14

Sprevak, Mark. "Computation and cognitive science." Studies in History and Philosophy of Science Part A 41, no. 3 (2010): 223–26. http://dx.doi.org/10.1016/j.shpsa.2010.07.011.

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15

Hussain, Amir. "Cognitive Computation: An Introduction." Cognitive Computation 1, no. 1 (2009): 1–3. http://dx.doi.org/10.1007/s12559-009-9013-z.

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16

Arsenijevic, Boban. "From Spatial Cognition to Language." Biolinguistics 2, no. 1 (2008): 003–23. http://dx.doi.org/10.5964/bioling.8615.

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Анотація:

The evolution of language has been linked in the recent research to the evolution of a number of different capacities, from the theory of mind to the type-recursive computation. In this paper, I examine the possibility that language has evolved from the capacity of spatial computation. Similarities, but also certain differences, between the two capacities are outlined and discussed, including the following. From the aspect of neuro-cognitive science, it cannot stay unnoticed that some of the central computations both in the language faculty and in the spatial cognition are located in the same

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17

Müller, Vincent C., and Matej Hoffmann. "What Is Morphological Computation? On How the Body Contributes to Cognition and Control." Artificial Life 23, no. 1 (2017): 1–24. http://dx.doi.org/10.1162/artl_a_00219.

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Анотація:

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “offloading computation from the brain to the body,” where the body is said to perform “morphological computation.” Our investigation of four characteristic cases of morphological computation in animals and robots shows that the “offloading” perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) morphology that facilitates control, (2) morphology that facil

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18

Dodig-Crnkovic, Gordana. "Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence." Proceedings 47, no. 1 (2020): 30. http://dx.doi.org/10.3390/proceedings2020047030.

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Анотація:

According to the currently dominant view, cognitive science is a study of mind and intelligence focused on computational models of knowledge in humans. It is described in terms of symbol manipulation over formal language. This approach is connected with a variety of unsolvable problems, as pointed out by Thagard. In this paper, I argue that the main reason for the inadequacy of the traditional view of cognition is that it detaches the body of a human as the cognizing agent from the higher-level abstract knowledge generation. It neglects the dynamical aspects of cognitive processes, emotions, c

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19

Dodig-Crnkovic, Gordana. "Morphological, Natural, Analog, and Other Unconventional Forms of Computing for Cognition and Intelligence." Proceedings 47, no. 1 (2020): 30. http://dx.doi.org/10.3390/proceedings47010030.

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Анотація:

According to the currently dominant view, cognitive science is a study of mind and intelligence focused on computational models of knowledge in humans. It is described in terms of symbol manipulation over formal language. This approach is connected with a variety of unsolvable problems, as pointed out by Thagard. In this paper, I argue that the main reason for the inadequacy of the traditional view of cognition is that it detaches the body of a human as the cognizing agent from the higher-level abstract knowledge generation. It neglects the dynamical aspects of cognitive processes, emotions, c

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20

DONG, ANDY. "Special Issue: Design computing and cognition." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19, no. 4 (2005): 227–28. http://dx.doi.org/10.1017/s0890060405050158.

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Анотація:

The field of research in design computing and cognition focuses on computational theories and systems that enact design. Design computing and cognition produces a unifying framework to model and explain design beyond the description of “design computing and cognition,” as in “design computing” and “design cognition” as two cognate disciplines. Research in design computing and cognition recognizes not only the essential relationship between human cognitive processes as models of computation but also how models of computation inspire conceptual realizations of human cognition in design. The arti

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21

Crutchfield, James P. "Dynamical embodiments of computation in cognitive processes." Behavioral and Brain Sciences 21, no. 5 (1998): 635. http://dx.doi.org/10.1017/s0140525x98291734.

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Dynamics is not enough for cognition, nor it is a substitute for information-processing aspects of brain behavior. Moreover, dynamics and computation are not at odds, but are quite compatible. They can be synthesized so that any dynamical system can be analyzed in terms of its intrinsic computational components.

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22

Esposito, Anna, Alessandro Vinciarelli, Simon Haykin, Amir Hussain, and Marcos Faundez-Zanuy. "Cognitive Computation Special Issue on Cognitive Behavioural Systems." Cognitive Computation 3, no. 3 (2011): 417–18. http://dx.doi.org/10.1007/s12559-011-9107-2.

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23

Fiorini, Rodolfo A. "Towards Advanced Quantum Cognitive Computation." International Journal of Software Science and Computational Intelligence 9, no. 1 (2017): 1–19. http://dx.doi.org/10.4018/ijssci.2017010101.

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Анотація:

Computational information conservation theory (CICT) can help us to develop competitive applications and even advanced quantum cognitive computational application and systems towards deep computational cognitive intelligence. CICT new awareness of a discrete HG (hyperbolic geometry) subspace (reciprocal space, RS) of coded heterogeneous hyperbolic structures, underlying the familiar Q Euclidean (direct space, DS) system surface representation can open the way to holographic information geometry (HIG) to recover lost coherence information in system description and to develop advanced quantum co

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24

Barrett, H. Clark. "Enzymatic Computation and Cognitive Modularity." Mind and Language 20, no. 3 (2005): 259–87. http://dx.doi.org/10.1111/j.0268-1064.2005.00285.x.

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25

Clark, Andy, Zenon W. Pylyshyn, and Alvin T. Goldman. "Computation and Cognition: Toward a Foundation for Cognitive Science." Philosophical Quarterly 38, no. 153 (1988): 526. http://dx.doi.org/10.2307/2219716.

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26

Ward, Nigel. "Computation and cognition: Toward a foundation for cognitive science." Artificial Intelligence 33, no. 3 (1987): 415–17. http://dx.doi.org/10.1016/0004-3702(87)90045-2.

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27

Mackworth, Alan K. "Computation and cognition: Toward a fundation for cognitive science." Artificial Intelligence 38, no. 2 (1989): 239–40. http://dx.doi.org/10.1016/0004-3702(89)90060-x.

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28

Stefik, Mark. "Computation and cognition: Toward a foundation of cognitive science." Artificial Intelligence 38, no. 2 (1989): 241–47. http://dx.doi.org/10.1016/0004-3702(89)90061-1.

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29

Piccinini, Gualtiero, and Sonya Bahar. "Neural Computation and the Computational Theory of Cognition." Cognitive Science 37, no. 3 (2012): 453–88. http://dx.doi.org/10.1111/cogs.12012.

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30

Awwad, Mohamad. "ON COMPUTATIONALISM: FORMAL INTERPRETATION AND INITIAL MODEL." Bulletin of Taras Shevchenko National University of Kyiv. Philosophy, no. 8 (2023): 5–8. http://dx.doi.org/10.17721/2523-4064.2023/8-1/8.

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Анотація:

In this article, we propose an initial formal model of computationalism based on mathematical relations between cognition and computation. More specifically, based on a set of cognitive constituents as a domain, and a set of computational implementations as a range, we define two relations of transformation over these sets. Moreover, we define the principles of implementability, describability, and phenomena correspondence, and we conjecture that full computationalism does not hold since these principles are not fulfilled. Particularly, many cognitively-tied phenomena fail to respect the descr

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31

HAMANN, HEIKO, and HEINZ WÖRN. "EMBODIED COMPUTATION." Parallel Processing Letters 17, no. 03 (2007): 287–98. http://dx.doi.org/10.1142/s0129626407003022.

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Анотація:

The traditional computational devices and models, such as the von Neumann architecture or the Turing machine, are strongly influenced by concepts of central control and perfection. The standard models of computation seem to cover the reality of computation only partially and lack, in particular, in the ability to describe more natural forms of computation. In this paper we propose the concept of embodied computation, a straight forward advancement of well known concepts such as amorphous computing, emergent phenomena and embodied cognitive science. Many embodied microscopic computational devic

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32

Ernst, Udo, David Rotermund, and Klaus Pawelzik. "Efficient Computation Based on Stochastic Spikes." Neural Computation 19, no. 5 (2007): 1313–43. http://dx.doi.org/10.1162/neco.2007.19.5.1313.

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The speed and reliability of mammalian perception indicate that cortical computations can rely on very few action potentials per involved neuron. Together with the stochasticity of single-spike events in cortex, this appears to imply that large populations of redundant neurons are needed for rapid computations with action potentials. Here we demonstrate that very fast and precise computations can be realized also in small networks of stochastically spiking neurons. We present a generative network model for which we derive biologically plausible algorithms that perform spike-by-spike updates of

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33

Miyashita, Yasushi. "Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit." Annual Review of Neuroscience 47, no. 1 (2024): 211–34. http://dx.doi.org/10.1146/annurev-neuro-081623-091311.

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Анотація:

The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded

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34

Clohessy, Anne Boylan, Michael I. Posner, Mary K. Rothbart, and Shaun P. Vecera. "The Development of Inhibition of Return in Early Infancy." Journal of Cognitive Neuroscience 3, no. 4 (1991): 345–50. http://dx.doi.org/10.1162/jocn.1991.3.4.345.

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Анотація:

The posterior visual spatial attention system involves a number of separable computations that allow orienting to visual locations. We have studied one of these computations, inhibition of return, in 3-, 4-, 6-, 12-, and 18--month-old infants and adults. Our results indicate that this computation develops rapidly between 3 and 6 months, in conjunction with the ability to program eye movements to specific locations. These findings demonstrate that an attention computation involving the mid-brain eye movement system develops after the third month of life. We suggest how this development might in

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35

Pylyshyn, Zenon. "On computation and cognition: Toward a foundation of cognitive science." Artificial Intelligence 38, no. 2 (1989): 248–51. http://dx.doi.org/10.1016/0004-3702(89)90062-3.

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36

Mikhailov, Igor F. "Computational Knowledge Representation in Cognitive Science." Epistemology & Philosophy of Science 56, no. 3 (2019): 138–52. http://dx.doi.org/10.5840/eps201956355.

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Анотація:

Cognitive research can contribute to the formal epistemological study of knowledge representation inasmuch as, firstly, it may be regarded as a descriptive science of the very same subject as that, of which formal epistemology is a normative one. And, secondly, the notion of representation plays a constitutive role in both disciplines, though differing therein in shades of its meaning. Representation, in my view, makes sense only being paired with computation. A process may be viewed as computational if it adheres to some algorithm and is substrate-independent. Traditionally, psychology is not

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37

Valiant, Leslie G. "A neuroidal architecture for cognitive computation." Journal of the ACM 47, no. 5 (2000): 854–82. http://dx.doi.org/10.1145/355483.355486.

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38

Horowitz, Amir. "Computation, External Factors, and Cognitive Explanations." Philosophical Psychology 20, no. 1 (2007): 65–80. http://dx.doi.org/10.1080/09515080601085856.

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39

Gregson, Robert A. M. "Nonlinear computation and dynamic cognitive generalities." Behavioral and Brain Sciences 20, no. 4 (1997): 688–89. http://dx.doi.org/10.1017/s0140525x97271608.

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Анотація:

Although one can endorse the complexity of the data and processes that Phillips & Singer (P&S) review, their mathematical suggestions can be compared critically with cases in nonlinear psychophysics, where the theoretician is faced with analogous problems. Owing to P&S's failure adequately to recognise both the intricate properties of nonlinear dynamics in networks and the constraints of metabolic demands on the temporal generation of patterns in biological nets their conclusions fail to meet the problems they properly address.

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40

Lloyd, Robert, and Hartwell Hooper. "URBAN COGNITIVE MAPS: COMPUTATION AND STRUCTURE." Professional Geographer 43, no. 1 (1991): 15–28. http://dx.doi.org/10.1111/j.0033-0124.1991.00015.x.

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41

Forbus, Kenneth D., Chen Liang, and Irina Rabkina. "Representation and Computation in Cognitive Models." Topics in Cognitive Science 9, no. 3 (2017): 694–718. http://dx.doi.org/10.1111/tops.12277.

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42

Oren, Sigal. "Economics and computation meets cognitive biases." ACM SIGecom Exchanges 20, no. 1 (2022): 67–69. http://dx.doi.org/10.1145/3572885.3572892.

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43

Piccinini, Gualtiero. "Computation and Representation in Cognitive Neuroscience." Minds and Machines 28, no. 1 (2018): 1–6. http://dx.doi.org/10.1007/s11023-018-9461-x.

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44

Day, Matthew. "Religion, Off-Line Cognition and the Extended Mind." Journal of Cognition and Culture 4, no. 1 (2004): 101–21. http://dx.doi.org/10.1163/156853704323074778.

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AbstractThis essay argues that the "classical" or "standard" computation model of an enviroment of thought may hamstring the nascent cognitive science of religion by masking the ways in which the bare biological brain is prosthetically extended and embedded in the surrounding landscape. The motivation for distinsuishing between the problem-solving profiles of the basic brain and the brain-plus-scaffolding is that in many domains non-biological artifacts support and augment biological modes of computation - often allowing us to overcome some of the brain's native computation limitations. The re

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45

Divyashree, M., H. G. Rangaraju, and C. R. Revanna. "Multi-objective optimized task scheduling in cognitive internet of vehicles: towards energy-efficiency." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 1 (2025): 1229–41. https://doi.org/10.11591/ijece.v15i1.pp1229-1241.

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Анотація:

The rise of intelligent and connected vehicles has led to new vehicularapplications, but vehicle computing capabilities remain limited. Mobileedge computing (MEC) can mitigate this by offloading computation tasksto the network's edge. However, limited computational capacities invehicles lead to increased latency and energy consumption. To address this,roadside units (RSUs) with cloud servers, known as edge computingdevices (ECDs), can be expanded to provide energy-efficient schedulingfor task computation. A new energy-efficient scheduling method calledmulti-objective optimization energy comput

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46

Wilson, Robert A. "What Computations (Still, Still) Can't Do: Jerry Fodor on Computation and Modularity." Canadian Journal of Philosophy Supplementary Volume 30 (2004): 407–25. http://dx.doi.org/10.1080/00455091.2004.10717612.

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Jerry Fodor's The Mind Doesn't Work That Way (2000; hereafter Mind) purports to do a number of things. To name three: First, it aims to show what is problematic about recent evolutionary psychology, especially as popularized in Steven Pinker's How the Mind Works (1997). Fodor's particular target here is the rose-coloured view of evolutionary psychology as offering a “new synthesis” in integrating computational psychology with evolutionary theory. Second, Fodor's book poses a series of related, in-principle problems for any cognitive theory that revolve around the putative tension between the l

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47

Divyashree, M., H. G. Rangaraju, and C. R. Revanna. "Multi-objective optimized task scheduling in cognitive internet of vehicles: towards energy-efficiency." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 1 (2025): 1229. http://dx.doi.org/10.11591/ijece.v15i1.pp1229-1241.

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The rise of intelligent and connected vehicles has led to new vehicular applications, but vehicle computing capabilities remain limited. Mobile edge computing (MEC) can mitigate this by offloading computation tasks to the network's edge. However, limited computational capacities in vehicles lead to increased latency and energy consumption. To address this, roadside units (RSUs) with cloud servers, known as edge computing devices (ECDs), can be expanded to provide energy-efficient scheduling for task computation. A new energy-efficient scheduling method called multi-objective optimization energ

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48

der van Velde, Frank. "Association and computation with cell assemblies." Behavioral and Brain Sciences 18, no. 4 (1995): 643–44. http://dx.doi.org/10.1017/s0140525x0004036x.

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AbstractThe cell assembly is an important concept for cognitive psychology. Cognitive processing will to a large extent depend on the relations that can exist between different assemblies. A potential relation between assemblies can already be seen in the occurrence of (classical) conditioning. However, the resulting associations between assemblies only produce behavioristic processing or so-called regular computation. Higher-level cognitive abilities most likely result from nonregular computation. I discuss the possibility of this form of computation in terms of cell assemblies.

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49

Turnbull, William. "Review of Computation and cognition: Toward a foundation for cognitive science." Canadian Psychology/Psychologie canadienne 27, no. 1 (1986): 85–87. http://dx.doi.org/10.1037/h0084465.

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Wang, Yingxu. "On the Mathematical Theories and Cognitive Foundations of Information." International Journal of Cognitive Informatics and Natural Intelligence 9, no. 3 (2015): 42–64. http://dx.doi.org/10.4018/ijcini.2015070103.

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A recent discovery in computer and software sciences is that information in general is a deterministic abstract quantity rather than a probability-based property of the nature. Information is a general form of abstract objects represented by symbolical, mathematical, communication, computing, and cognitive systems. Therefore, information science is one of the contemporary scientific disciplines collectively known as abstract sciences such as system, information, cybernetics, cognition, knowledge, and intelligence sciences. This paper presents the cognitive foundations, mathematical models, and

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