Distributed Computation using Evolutionary Consciousness : An Approach
The modeling of biological phenomena and its adaptations to distributed computing are promising research areas. The computational modeling of neurobiological phenomena, such as cognition and consciousness, has potential for applications into bio-inspired distributed computing. The functioning of neu...
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| Published in: | International journal of computational intelligence systems Vol. 8; no. 5; pp. 928 - 942 |
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| Format: | Journal Article |
| Language: | English |
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Springer Netherlands
01.01.2015
Springer Nature B.V Atlantis Press Springer |
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| ISSN: | 1875-6891, 1875-6883, 1875-6883 |
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| Abstract | The modeling of biological phenomena and its adaptations to distributed computing are promising research areas. The computational modeling of neurobiological phenomena, such as cognition and consciousness, has potential for applications into bio-inspired distributed computing. The functioning of neurological structures is inherently distributed in nature having a closer match to distributed computing. This paper proposes a mathematical model of state of consciousness by following the functional neurophysiology as well as elements of distributed computing. The scopes of evolution of consciousness and memory are incorporated into the model. The nodal classifications and formation of structural hierarchy in distributed computing nodes by incorporating elements of cognitive model are investigated. Evaluation of the model is made by numerical simulation considering different choice functions. The results illustrate that, model of consciousness can be adapted to bio-inspired distributed computing structures and the gradual evolution of consciousness is deterministic under fair excitations from environment. |
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| AbstractList | The modeling of biological phenomena and its adaptations to distributed computing are promising research areas. The computational modeling of neurobiological phenomena, such as cognition and consciousness, has potential for applications into bio-inspired distributed computing. The functioning of neurological structures is inherently distributed in nature having a closer match to distributed computing. This paper proposes a mathematical model of state of consciousness by following the functional neurophysiology as well as elements of distributed computing. The scopes of evolution of consciousness and memory are incorporated into the model. The nodal classifications and formation of structural hierarchy in distributed computing nodes by incorporating elements of cognitive model are investigated. Evaluation of the model is made by numerical simulation considering different choice functions. The results illustrate that, model of consciousness can be adapted to bio-inspired distributed computing structures and the gradual evolution of consciousness is deterministic under fair excitations from environment. |
| Author | Bagchi, Susmit |
| Author_xml | – sequence: 1 givenname: Susmit surname: Bagchi fullname: Bagchi, Susmit email: susmitbagchi@yahoo.co.uk organization: School of Mechanical, Aerospace and Information Engineering Department of Aerospace and Software Engineering, Gyeongsang National University |
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| Keywords | Cognition consciousness bio-inspired computing distributed computing fuzzy logic |
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Ryali, S., Chen, T., Padmanabhan, A., Cai, W., Menon, V., Development and Validation of consensus clustering-based framework for brain segmentation using resting fMRI, Journal of Neuroscience Methods, Vol. 240, Elsevier, 2015, doi:https://doi.org/10.1016/j.jneumeth.2014.11.014. FitchWTNano-intentionality: A defense of intrinsic intentionalityBiology and Philosophy200823157177 Sporns, O., Networks of the brain, MIT Press, 2011. TononiGConsciousness as integrated information: A provisional manifestoThe Biological Bulletin20082153216242 AleksanderIModeling Consciousness in Virtual Computational MachinesSynthesis Philosophica2008222447454 KelleyRTavakkoliAKingCAmbardekarANicolescuMNicolescuMContext-based bayesian intent recognitionIEEE Transactions on Autonomous Mental Development20124215225 ArbibMACaplanDNeurolinguistics must be computationalBehavioral & Brain Sciences197923449483 Lin, J., Yang, J. 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| References_xml | – reference: LondonMHäusserMDendritic computationAnnual Review of Neuroscience200528503532 – reference: TononiGConsciousness as integrated information: A provisional manifestoThe Biological Bulletin20082153216242 – reference: Starzyk, J. A., and Prasad, D. K., A Computational model of machine consciousness, Int. J. Machine Consciousness, Vol. 3, No. 2, World Scientific, 2011. – reference: Taylor, J. G., A general framework for the functions of the brain, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, Vol. 1, IEEE, 2000, pp. 35–40. – reference: AleksanderIModeling Consciousness in Virtual Computational MachinesSynthesis Philosophica2008222447454 – reference: Sloman, A., Chrisley, R., Virtual machines and consciousness, Journal of Consciousness Studies, Vol. 10, No. 4–5, 2003, pp. 133–72. – reference: Mumford, D., Desolneux, A., Pattern Theory: The stochastic analysis of real-world signals, A K Peters Ltd., CRC Press, 2010. – reference: ManzottiRConsciousness and existence as a processMind and Matter200641743 – reference: Fitch, W. T., Toward a Computational Framework for Cognitive Biology: Unifying approaches from cognitive neuroscience and comparative cognition, Physics of Life Reviews, Elsevier, DOI: https://doi.org/10.1016/j.plrev.2014.04.005, 2014. – reference: WardLThe thalamic dynamic core theory of conscious experienceConsciousness and Cognition2011202464486 – reference: Breazeal, C., Buchsbaum, D., Gray, J., Gatenby, D., Blumberg, B., Learning from and about others: Towards using imitation to bootstrap the social understanding of others by robots, Artificial Life, Vol. 11, No. 1–2, 2005, pp. 31–62. – reference: El Boustani, S., Destexhe, A., A master equation formalism for macroscopic modeling of asynchronous irregular activity states, Neural Computation, Vol. 21(1), 2009, pp. 46–100. – reference: FeketeTEdelmanSTowards a computational theory of experienceConsciousness and Cognition, Elsevier201120807827 – reference: Koch, C., Tononi, G., Can machines be conscious?, IEEE Spectrum, (June), 2008, pp. 55–59. – reference: ChellaAGaglioSSynthetic phenomenology and high-dimensional buffer hypothesisInternational Journal of Machine Consciousness20124353365 – reference: Nehaniv, C., Dautenhahn, K. (Eds.)., Imitation and social learning in robots, humans, and animals: Behavioural, social and communicative dimensions, Cambridge University Press, 2007. – reference: Lin, J., Yang, J. G., Consciousness modeling : A neural computing approach, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, IEEE, 2004. – reference: FitchWTNano-intentionality: A defense of intrinsic intentionalityBiology and Philosophy200823157177 – reference: RamamurthyUFranklinSAgrawalPSelf-system in a model of cognitionInternational Journal of Machine Consciousness20124325333 – reference: BosseTJonkerCTreurJFormalization of Damasio’s theory of emotion, feeling and core consciousnessConsciousness and Cognition20081794113 – reference: KelleyRTavakkoliAKingCAmbardekarANicolescuMNicolescuMContext-based bayesian intent recognitionIEEE Transactions on Autonomous Mental Development20124215225 – reference: ReesGKreimanGKochCNeural correlates of consciousness in humansNature Reviews Neuroscience20023261270 – reference: MumfordDOn the computational architecture of the neocortex. II. The role of cortico-cortical loopsBiological Cybernetics1992663241251 – reference: FranklinDWWolpertDMComputational mechanisms of sensorimotor controlNeuron201172425442 – reference: Sporns, O., Networks of the brain, MIT Press, 2011. – reference: KelleyRKingCTavakkoliANicolescuMNicolescuMBebisGAn architecture for understanding intent using a novel hidden markov formulationInternational Journal of Humanoid Robotics20085203224 – reference: BaarsBFranklinSAn architectural model of conscious and unconscious brain functionNeural Networks200720955961 – reference: Phillips, A. W., Malsburg, C. V. D., Singer, W., Dynamic Coordination in the Brain –From Neurons to Mind, MIT Press, 2010, ISBN: 978-0-262-01471-7. – reference: Poeppel, D., Embick, D., Defining the relation between linguistics and neuroscience, Twenty-First Century Psycholinguistics: Four Cornerstones, Ed. A. Cutler, Lawrence Erlbaum, London, 2005, pp. 103–120. – reference: SethAKIzhikevichEMReekeGNEdelmanGMTheories and measures of consciousness: An extended frameworkProc. of National Academy of Sciences, USA2006103281079910804 – reference: ArbibMACaplanDNeurolinguistics must be computationalBehavioral & Brain Sciences197923449483 – reference: FitchWTFriedericiADHagoortPPattern Perception and Computational ComplexityPhilosophical Transactions of The Royal Society B201236719251932 – reference: Sun, R., Franklin, S., Computational models of consciousness, In P. Zelazo, & M. Moscovitch (Eds.), Cambridge handbook of consciousness, Cambridge University Press, 2007, pp. 151–174. – reference: HerzAGollischTMachensCKJaegerDModeling single-neuron dynamics and computations: A balance of detail and abstractionScience20063148085 – reference: ReggiaJAThe rise of machine consciousness: Studying consciousness with computational modelsNeural Networks, Elsevier201344112131 – reference: Rolls, E. T., Deco, G., Computational Neuroscience of Vision, Oxford University Press, Oxford, 2001. – reference: Kuipers, B., Consciousness: drinking from the firehose of experience, In Proceedings of 20th national conference on artificial intelligence, AI Press, 2005, pp. 1298–1305. – reference: BlockNTwo neural correlates of consciousnessTrends in Cognitive Sciences2005924652 – reference: Posner, J., Saper, C., Schiff, N., Plum, F., Plum and Posner’s diagnosis of stupor and coma, Oxford University Press, 2007. – reference: Rummelhart, D. E., McClelland, J. L., Parallel distributed processing: explorations in the microstructure of cognition, Vol. 1, Foundations, MIT Press, Cambridge, 1986. – reference: Atkinson, A. P., Thomas, M. S. C., Cleeremans, A., Consciousness: mapping the theoretical landscape, Trends in Cognitive Sciences, Vol 4, No. 10, 2000. – reference: Ryali, S., Chen, T., Padmanabhan, A., Cai, W., Menon, V., Development and Validation of consensus clustering-based framework for brain segmentation using resting fMRI, Journal of Neuroscience Methods, Vol. 240, Elsevier, 2015, doi:https://doi.org/10.1016/j.jneumeth.2014.11.014. – reference: Bonchek-DokowEKaminkaGATowards computational models of intention detection and intention predictionCognitive Systems Research, Elsevier2014284479 – ident: CIT0036 doi: 10.1017/CBO9780511489808 – volume: 22 start-page: 447 issue: 2 year: 2008 ident: CIT0006 publication-title: Synthesis Philosophica – ident: CIT0015 doi: 10.1093/acprof:oso/9780198524885.001.0001 – ident: CIT0032 doi: 10.1016/j.concog.2007.06.006 – ident: CIT0019 doi: 10.1073/pnas.0604347103 – ident: CIT0023 doi: 10.1142/S1793843012400185 – ident: CIT0021 doi: 10.1093/med/9780195321319.001.0001 – ident: CIT0025 doi: 10.1142/S1793843012400203 – ident: CIT0004 doi: 10.1016/S1364-6613(00)01533-3 – ident: CIT0016 doi: 10.1109/IJCNN.2000.857810 – ident: CIT0017 doi: 10.2307/25470707 – volume-title: A K Peters Ltd year: 2010 ident: CIT0012 – volume: 4 start-page: 7 issue: 1 year: 2006 ident: CIT0020 publication-title: Mind and Matter – volume-title: Proceedings of the Third International Conference on Machine Learning and Cybernetics year: 2004 ident: CIT0007 – ident: CIT0042 doi: 10.1016/j.jneumeth.2014.11.014 – volume: 10 start-page: 133 issue: 4 year: 2003 ident: CIT0022 publication-title: Journal of Consciousness Studies – ident: CIT0029 doi: 10.1016/j.neuron.2011.10.006 – ident: CIT0037 doi: 10.1109/TAMD.2012.2211871 – year: 2010 ident: CIT0043 – ident: CIT0035 doi: 10.1142/S0219843608001418 – start-page: 103 volume-title: Twenty-First Century Psycholinguistics: Four Cornerstones year: 2005 ident: CIT0010 – ident: CIT0014 doi: 10.1007/BF00198477 – ident: CIT0002 doi: 10.1016/j.neunet.2013.03.011 – ident: CIT0034 doi: 10.1162/neco.2009.02-08-710 – ident: CIT0018 doi: 10.1162/1064546053278955 – ident: CIT0031 doi: 10.1098/rstb.2012.0099 – ident: CIT0038 doi: 10.1017/CBO9780511816789.008 – ident: CIT0001 doi: 10.1016/j.plrev.2014.04.005 – ident: CIT0041 doi: 10.7551/mitpress/8476.001.0001 – volume: 20 start-page: 807 year: 2011 ident: CIT0003 publication-title: Elsevier – ident: CIT0039 doi: 10.7551/mitpress/5236.001.0001 – ident: CIT0027 doi: 10.1126/science.1127240 – ident: CIT0011 doi: 10.1016/j.tics.2004.12.006 – ident: CIT0033 doi: 10.1038/nrn783 – ident: CIT0009 doi: 10.1017/S0140525X0006369X – start-page: 1298 volume-title: Proceedings of 20th national conference on artificial intelligence year: 2005 ident: CIT0024 – ident: CIT0028 doi: 10.1007/s10539-007-9079-5 – ident: CIT0013 doi: 10.1016/j.concog.2011.01.007 – ident: CIT0005 doi: 10.1016/j.cogsys.2013.07.004 – ident: CIT0008 doi: 10.1142/S1793843011000819 – ident: CIT0040 doi: 10.1016/j.neunet.2007.09.013 – ident: CIT0026 doi: 10.1146/annurev.neuro.28.061604.135703 |
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| SubjectTerms | bio-inspired computing Biological models (mathematics) Biomimetics Cognition Cognitive science Computer networks Computer Science Consciousness distributed computing Distributed processing Evolutionary algorithms fuzzy logic Mathematics Neurophysiology Research Article Structural hierarchy |
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| Title | Distributed Computation using Evolutionary Consciousness : An Approach |
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