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Impresjony słów. Język naturalnych i sztucznych sieci neuronowych

Data publikacji: 29.03.2019

Rocznik Kognitywistyczny, 2018, Tom 11, s. 55 - 75

https://doi.org/10.4467/20843895RK.18.005.9759

Autorzy

Wiesław Galus
Niezależny badacz
https://orcid.org/0000-0002-5415-5804 Orcid
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Tytuły

Impresjony słów. Język naturalnych i sztucznych sieci neuronowych

Abstrakt

It was shown that mental representations of objects created in human minds during the learning process, which take the form of hierarchically connected neurons called semblions, have properties explaining the hierarchical structure of metaphors and other mind tools embodied in Lakoff’s cognitive linguistics concept. It was proven that, at the neurological level, semblions of objects, concepts, ideas and models can be associated with neuronal representations of phonemes heard in coincidence with other objects, creating new semblions which correspond to words. It was shown how activation of semblions can result in recalling, associating, thinking and other higher mental functions which are necessary to use natural language. It was considered why semblions representing mathematical notions enable an adequate description of numerous phenomena of the physical world but, at the same time, their polymodal counterparts can be used to describe qualia. The complementarity between Horzyk’s associative intelligence model and Galus’ model of architecture of self-aware systems was pointed out, which can be used to create artificial self-aware systems able to use both natural language and formal languages with understanding.

Bibliografia

Aur, D. i Jog, M.S. (2006). Building spike representation in tetrodes. Journal of Neuroscience Methods, 157(2): 364–373.

Aur, D. i Jog, M.S. (2007). Neuronal spatial learning. Neural Processing Letters, 25(1): 31–47.

Aur, D. i Jog, M.S. (2010). Neuroelectrodynamics – Understanding the Brain Language. Amsterdam: IOS Press.

Benjamin, B.V., Gao, P., McQuinn, E., Choudhary, S., Chandrasekaran, A.R., Bussat, J.-M., AlvarezIcaza, R., Arthur, J.V., Merolla, P.A. i Boahen, K. (2014). Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations. Proceedings of the IEEE, 102(5), May.

Bonini, C.P. (1963). Simulation of Information and Decision Systems in the Firm. Englewood Cliff s, NJ: Prentice-Hall.

Brożek, B., Hohol, M. (2014). Umysł matematyczny. Kraków: Copernicus Center Press.

Chomsky, N. (1982). Zagadnienia teorii składni. Wrocław: Ossolineum.

Dinstein, I., Th omas, C., Behrmann, M. i Heeger, D.J. (2008). A mirror up to nature. Current Biology, 18(1): R13–18.

Di Pellegrino, G., Fadiga, L., Fogassi, L., Gallese, V., Rizzolatti, G. (1992). Understanding motor events: a neurophysiological study. Experimental Brain Research, 91: 176–180.

Gallese, V., Fadiga, L., Fogassi, L. i Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119(2): 593–609.

Gallese, V. i Goldman, A. (1998). Mirror neurons and the simulation theory of mind-reading. Trends in Cognitive Sciences, 2(12).

Gallese, V. (2009). Ucieleśniona symulacja: Od neuronów po doświadczenie fenomenologiczne. W: A. Klawiter (red.). Formy aktywności umysłu. Ujęcie kognitywistyczne, t. 2: Ewolucja i złożone struktury poznawcze. Warszawa: Wydawnictwo Naukowe PWN.

Feldman, J. i Narayanan, S. (2004). Embodied meaning in a neural theory of language. Brain and Language, 89(2): 385–392.

Galus, W.L. (2015a). Architektura świadomości. Część I: Logika i morfologia sieci neuronowej. Roczniki Filozofi czne, 63(1): 139–171.

Galus, W.L. (2015b). Architektura świadomości. Część II: Struktura molekularna i biofizyka pamięci. Roczniki Filozofi czne, 63(2): 237–261.

Galus, W.L. (2015c). Architektura świadomości. Część III: Wola i sens istnienia. Roczniki Filozoficzne, 63(3).

Galus, W.L. i Starzyk, J. (2018). Świadomość? Ależ to bardzo proste! Warszawa: BEL Studio.

Graham, J., Starzyk, J.A. i Jachyra, D. (2015). Opportunistic behavior in motivated learning agents. IEEE Transactions on Neural Networks and Learning Systems, 26(8): 1735–1746.

Heller, M. (2016). Filozofi a nauki, wyd. III. Kraków: Petrus.

Hickok, G. (2009). Eight problems for the mirror neuron theory of action understanding in monkeys and humans. Journal of Cognitive Neuroscience, 21(7): 1229–1243.

Horzyk, A. (2013). Sztuczne systemy skojarzeniowe i asocjacyjna sztuczna inteligencja. Akademicka Oficyna Wydawnicza EXIT, Warszawa.

Jog, M.S., Aur, D. i Connolly, C.I. (2007). Is there a tipping point in neuronal ensembles during learning? Neuroscience Letters, 412(1): 39–44.

Jog, M.S. i Aur, D. (2009). A theoretical information processing-based approach to basal ganglia function. Advances in Behavioral Biology, 58, Part 2: 211–222.

Lakoff , G. (1987). Women, Fire and Other Dangerous Th ings: What Categories Reveal about the Mind. Chicago: University of Chicago Press.

Lakoff , G. i Johnson, M. (1999). Philosophy in the Flesh: Th e Embodied Mind and It’s Challenge to Western Th ought. New York: Basic Book.

Lakoff , G. i Johnson, M. (2010). Metafory w naszym życiu. Warszawa: Aletheia.

Lakoff , G. i Núñez, R.E. (2000). Where Mathematics Comes From: How the Embodied Brain Brings Mathematics into Being. New York: Basic Books.

Merolla, P., Arthur, J., Alvarez, R., Bussat, J.-M. i Boahen, K. (2014). A multicast tree router for multichip neuromorphic systems. IEEE Transactions on Circuits and Systems I: Regular Papers, 61(3).

Minsky, M. (1980). K-Lines: A theory of memory. Cognitive Science, 4: 117–l33.

Pascolo, P.B., Ragogna, R. i Rossi, R. (2009). Th e mirror-neuron system paradigm and its consistency. Gait Posture, 30(Suppl. 1): 65.

Pawelec, A. (2005). Znaczenie ucieleśnione. Propozycje kręgu Lakoff a. Kraków: Universitas.

Perlovsky, L.I. (1998). Conundrum of combinatorial complexity. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(6), June.

Perlovsky, L.I. (2001). Neural Networks and Intellect: Using Model Based Concepts. New York: Oxford University Press.

Perlovsky, L.I. (2007). Th e knowledge instinct. W: L.I. Perlovsky, R. Kozma (red.). Neurodynamics of Cognition and Consciousness: Understanding Complex Systems. New York: Springer.

Pulvermueller, F. (2001). Brain refl ection of words and their meaning. Trends in Cognitive Sciences, 5(12).

Quiroga, R.Q., Fried, I. i Koch, Ch. (2013). Brain cells for grandmother. Scientifi c American.com, 31 February.

Quiroga, R.Q., Reddy, L., Kreiman, G., Koch, C. i Fried, I. (2005). Invariant visual representation by single neurons in the human brain. Nature, 435(7045): 1102–1107.

Ramachandran, V.S. (2012). Neuronauka o podstawach człowieczeństwa. O czym mówi mózg? Warszawa: Wydawnictwa Uniwersytetu Warszawskiego.

Rizzolatti, G. i in. (1996). Premotor cortex and the recognition of motor actions. Cognitive Brain Research, 3: 131–141.

Starzyk, J.A. (2011). Motivated learning for computational intelligence. W: B. Igelnik (red.). Computational Modeling and Simulation of Intellect: Current State and Future Perspectives. Hershey, PA: IGI Publishing.

Starzyk, J.A., i Graham, J. (2015). MLECOG – Motivated Learning Embodied Cognitive Architecture. IEEE Systems Journal, July. Dostępny online: 10.1109/JSYST.2015.2442995.

Starzyk, J.A., Graham, J.T., Raif, P. i Tan, A.-H. (2012). Motivated learning for autonomous robots development. Cognitive Science Research, 14(1): 10–25.

Vadakkan, K.I. (2011). Processing semblances induced through inter-postsynaptic functional LINKs, presumed biological parallels of K-lines proposed for building artifi cial intelligence. Frontiers in Neuroengineering, 4(8).

Vadakkan, K.I. (2012a). Framework of consciousness from semblance of activity at functionally LINKed postsynaptic membranes. Frontiers in Psychology, 1: 168.

Vadakkan, K.I. (2012b). The nature of “internal sensations” of higher brain functions may be derived from the design rules for artifi cial machines that can produce them. Journal of Biological Engineering, 6(1): 21.

Waal, F. de (2014). Bonobo i ateista. W poszukiwaniu humanizmu wśród naczelnych. Kraków: Copernicus Center Press.

Informacje

Informacje: Rocznik Kognitywistyczny, 2018, Tom 11, s. 55 - 75

Typ artykułu: Oryginalny artykuł naukowy

Tytuły:

Polski:

Impresjony słów. Język naturalnych i sztucznych sieci neuronowych

Angielski:

Semblions of Words. The Language of Artificial and Natural Neural Networks

Publikacja: 29.03.2019

Status artykułu: Otwarte __T_UNLOCK

Licencja: CC BY-NC-ND  ikona licencji

Udział procentowy autorów:

Wiesław Galus (Autor) - 100%

Korekty artykułu:

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Języki publikacji:

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