Academic literature on the topic 'Algorithme cognitif'
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Journal articles on the topic "Algorithme cognitif":
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Jalenques, I. "SMP – Diagnostic et traitement personnalisés : un paradigme d’avenir dans les troubles schizophréniques." European Psychiatry 29, S3 (November 2014): 591–92. http://dx.doi.org/10.1016/j.eurpsy.2014.09.315.
Abstract:
L’objectif d’un diagnostic et d’un programme thérapeutique personnalisés pour chaque patient souffrant de troubles schizophréniques n’est aujourd’hui qu’en partie atteint. Cette session fait le point sur les dernières avancées et celles à venir concernant les outils et stratégies diagnostiques ainsi que les thérapeutiques médicamenteuses et cognitives.Si l’hétérogénéité des tableaux cliniques répondant aux critères diagnostiques de schizophrénie est une constatation bien établie, on ne sait pas encore clairement ce que recouvre cette hétérogénéité : maladies distinctes ou variabilité d’expression d’une même maladie. Outre l’intérêt théorique, identifier une étiologie revêt un intérêt pratique pour définir la stratégie thérapeutique la plus adaptée chez un patient donné car certaines caractéristiques cognitives ou évolutives ont une incidence sur les options thérapeutiques. Reste à déterminer un algorithme réaliste permettant de hiérarchiser outils et examens pour affiner le bilan diagnostique de l’ensemble des patients.L’évolution des troubles schizophréniques a été amplement modifiée suite à l’avènement des neuroleptiques en 1952. Les antipsychotiques de seconde génération sont venus compléter l’offre de soins. Les données récentes insistent sur la nécessité de traiter sans retard car la souffrance engendrée par la maladie est réelle. Avec les nouvelles molécules la prise en charge devrait être individualisée, prenant en compte les attentes et appréhensions des patients notamment face au traitement pharmacologique.Les troubles cognitifs très fréquents, hétérogènes, contribuent fortement au pronostic fonctionnel. Le profil des compétences dégradées et préservées est propre à chaque patient : une remédiation cognitive pertinente nécessite donc des prises en charge individualisées. Le bilan neuropsychologique, dans le cadre d’une évaluation intégrative multidisciplinaire, permet d’établir des liens entre les profils cognitif et fonctionnel. Les éventuelles indications de remédiation cognitive qui en découlent ne doivent pas viser l’amélioration des performances cognitives pour elles-mêmes, mais la réussite de projets concrets dans les domaines social ou professionnel à laquelle cette amélioration peut contribuer [1,2].
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Diederichs, Elmar. "Reinforcement Learning - A Technical Introduction." Journal of Autonomous Intelligence 2, no. 2 (August 19, 2019): 25. http://dx.doi.org/10.32629/jai.v2i2.45.
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Reinforcement learning provides a cognitive science perspective to behavior and sequential decision making provided that RL-algorithms introduce a computational concept of agency to the learning problem. Hence it addresses an abstract class of problems that can be characterized as follows: An algorithm confronted with information from an unknown environment is supposed to find stepwise an optimal way to behave based only on some sparse, delayed or noisy feedback from some environment, that changes according to the algorithm's behavior. Hence reinforcement learning offers an abstraction to the problem of goal-directed learning from interaction. The paper offers an opintionated introduction in the algorithmic advantages and drawbacks of several algorithmic approaches such that one can understand recent developments and open problems in reinforcement learning.
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Anderson, John R. "Methodologies for studying human knowledge." Behavioral and Brain Sciences 10, no. 3 (September 1987): 467–77. http://dx.doi.org/10.1017/s0140525x00023554.
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AbstractThe appropriate methodology for psychological research depends on whether one is studying mental algorithms or their implementation. Mental algorithms are abstract specifications of the steps taken by procedures that run in the mind. Implementational issues concern the speed and reliability of these procedures. The algorithmic level can be explored only by studying across-task variation. This contrasts with psychology's dominant methodology of looking for within-task generalities, which is appropriate only for studying implementational issues.The implementation-algorithm distinction is related to a number of other “levels” considered in cognitive science. Its realization in Anderson's ACT theory of cognition is discussed. Research at the algorithmic level is more promising because it is hard to make further fundamental scientific progress at the implementational level with the methodologies available. Protocol data, which are appropriate only for algorithm-level theories, provide a richer source than data at the implementational level. Research at the algorithmic level will also yield more insight into fundamental properties of human knowledge because it is the level at which significant learning transitions are defined.The best way to study the algorithmic level is to look for differential learning outcomes in pedagogical experiments that manipulate instructional experience. This provides control and prediction in realistically complex learning situations. The intelligent tutoring paradigm provides a particularly fruitful way to implement such experiments.The implications of this analysis for the issue of modularity of mind, the status of language, research on human/computer interaction, and connectionist models are also examined.
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Foley, J. M., M. J. Wright, A. L. Gooding, M. Ettenhofer, M. Kim, M. Choi, S. A. Castellon, et al. "Operationalization of the updated diagnostic algorithm for classifying HIV-related cognitive impairment and dementia." International Psychogeriatrics 23, no. 5 (November 19, 2010): 835–43. http://dx.doi.org/10.1017/s1041610210002085.
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ABSTRACTBackground: This study applies the updated HIV-Associated Neurocognitive Disorders (HAND) diagnostic algorithm.Methods: Participants were 210 HIV-infected-adults, classified using proposed HAND criteria: HIV-Associated Dementia (HAD), Mild Neurocognitive Disorder (MND), Asymptomatic Neurocognitive Impairment (ANI).Results: The algorithm yielded: normal = 32.8%, ANI = 21.4%, MND = 34.3%, and HAD = 11.4%. Normal participants performed superior to HAND-defined participants on cognition, and HAD participants performed more poorly on global cognition and executive functioning. Two distinct subgroups of interest emerged: (1) functional decline without cognitive impairment; (2) severe cognitive impairment and minimal functional compromise.Conclusions: The algorithm discriminates between HIV-infected cognitively impaired individuals. Diagnosis yields two unique profiles requiring further investigation. Findings largely support the algorithm's utility for diagnosing HIV-cognitive-impairment, but suggest distinct subsets of individuals with discrepant cognitive/functional performances that may not be readily apparent by conventional application of HAND diagnosis.
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Gonda, Dalibor, Viliam Ďuriš, Anna Tirpáková, and Gabriela Pavlovičová. "Teaching Algorithms to Develop the Algorithmic Thinking of Informatics Students." Mathematics 10, no. 20 (October 18, 2022): 3857. http://dx.doi.org/10.3390/math10203857.
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Modernization and the ever-increasing trend of introducing modern technologies into various areas of everyday life require school graduates with programming skills. The ability to program is closely related to computational thinking, which is based on algorithmic thinking. It is well known that algorithmic thinking is the ability of students to work with algorithms understood as a systematic description of problem-solving strategies. Algorithms can be considered as a fundamental phenomenon that forms a point of contact between mathematics and informatics. As part of an algorithmic graph theory seminar, we conducted an experiment where we solved the knight’s tour problem using the backtracking method to observe the change in students’ motivation to learn algorithms at a higher cognitive level. Seventy-four students participated in the experiment. Statistical analysis of the results of the experiment confirmed that the use of the algorithm with decision-making in teaching motivated students to learn algorithms with understanding.
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Lee, Won Hee. "The Choice of Machine Learning Algorithms Impacts the Association between Brain-Predicted Age Difference and Cognitive Function." Mathematics 11, no. 5 (March 2, 2023): 1229. http://dx.doi.org/10.3390/math11051229.
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Machine learning has been increasingly applied to neuroimaging data to compute personalized estimates of the biological age of an individual’s brain (brain age). The difference between an individual’s brain-predicted age and their chronological age (brainPAD) is used as a biomarker of brain aging and disease, but the potential contribution of different machine learning algorithms used for brain age prediction to the association between brainPAD and cognitive function has not been investigated yet. Here, we applied seven commonly used algorithms to the same multimodal brain imaging data (structural and diffusion MRI) from 601 healthy participants aged 18–88 years in the Cambridge Centre for Ageing and Neuroscience to assess variations in brain-predicted age. The inter-algorithm similarity in brain-predicted age and brain regional regression weights was examined using the Pearson’s correlation analyses and hierarchical clustering. We then assessed to what extent machine learning algorithms impact the association between brainPAD and seven cognitive variables. The regression models achieved mean absolute errors of 5.46–7.72 years and Pearson’s correlation coefficients of 0.86–0.92 between predicted brain age and chronological age. Furthermore, we identified a substantial difference in linking brainPAD to cognitive measures, indicating that the choice of algorithm could be an important source of variability that confounds the relationship between brainPAD and cognition.
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Wahn, Basil, Laura Schmitz, Frauke Nora Gerster, and Matthias Weiss. "Offloading under cognitive load: Humans are willing to offload parts of an attentionally demanding task to an algorithm." PLOS ONE 18, no. 5 (May 19, 2023): e0286102. http://dx.doi.org/10.1371/journal.pone.0286102.
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In the near future, humans will increasingly be required to offload tasks to artificial systems to facilitate daily as well as professional activities. Yet, research has shown that humans are often averse to offloading tasks to algorithms (so-called “algorithmic aversion”). In the present study, we asked whether this aversion is also present when humans act under high cognitive load. Participants performed an attentionally demanding task (a multiple object tracking (MOT) task), which required them to track a subset of moving targets among distractors on a computer screen. Participants first performed the MOT task alone (Solo condition) and were then given the option to offload an unlimited number of targets to a computer partner (Joint condition). We found that participants significantly offloaded some (but not all) targets to the computer partner, thereby improving their individual tracking accuracy (Experiment 1). A similar tendency for offloading was observed when participants were informed beforehand that the computer partner’s tracking accuracy was flawless (Experiment 2). The present findings show that humans are willing to (partially) offload task demands to an algorithm to reduce their own cognitive load. We suggest that the cognitive load of a task is an important factor to consider when evaluating human tendencies for offloading cognition onto artificial systems.
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Amoore, Louise, and Rita Raley. "Securing with algorithms: Knowledge, decision, sovereignty." Security Dialogue 48, no. 1 (December 12, 2016): 3–10. http://dx.doi.org/10.1177/0967010616680753.
Abstract:
Amid the deployment of algorithmic techniques for security – from the gathering of intelligence data to the proliferation of smart borders and predictive policing – what are the political and ethical stakes involved in securing with algorithms? Taking seriously the generative and world-making capacities of contemporary algorithms, this special issue draws attention to the embodied actions of algorithms as they extend cognition, agency and responsibility beyond the conventional sites of the human, the state and sovereignty. Though focusing on different modes of algorithmic security, each of the contributions to the special issue shares a concern with what it means to claim security on the terrain of incalculable and uncertain futures. To secure with algorithms is to reorient the embodied relation to uncertainty, so that human and non-human cognitive beings experimentally generate and learn what to bring to the surface of attention for a security action.
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Dangi, Siddharth, Amy L. Orsborn, Helene G. Moorman, and Jose M. Carmena. "Design and Analysis of Closed-Loop Decoder Adaptation Algorithms for Brain-Machine Interfaces." Neural Computation 25, no. 7 (July 2013): 1693–731. http://dx.doi.org/10.1162/neco_a_00460.
Abstract:
Closed-loop decoder adaptation (CLDA) is an emerging paradigm for achieving rapid performance improvements in online brain-machine interface (BMI) operation. Designing an effective CLDA algorithm requires making multiple important decisions, including choosing the timescale of adaptation, selecting which decoder parameters to adapt, crafting the corresponding update rules, and designing CLDA parameters. These design choices, combined with the specific settings of CLDA parameters, will directly affect the algorithm's ability to make decoder parameters converge to values that optimize performance. In this article, we present a general framework for the design and analysis of CLDA algorithms and support our results with experimental data of two monkeys performing a BMI task. First, we analyze and compare existing CLDA algorithms to highlight the importance of four critical design elements: the adaptation timescale, selective parameter adaptation, smooth decoder updates, and intuitive CLDA parameters. Second, we introduce mathematical convergence analysis using measures such as mean-squared error and KL divergence as a useful paradigm for evaluating the convergence properties of a prototype CLDA algorithm before experimental testing. By applying these measures to an existing CLDA algorithm, we demonstrate that our convergence analysis is an effective analytical tool that can ultimately inform and improve the design of CLDA algorithms.
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Ionescu, Claudiu Gabriel, and Monica Licu. "Are TikTok Algorithms Influencing Users’ Self-Perceived Identities and Personal Values? A Mini Review." Social Sciences 12, no. 8 (August 21, 2023): 465. http://dx.doi.org/10.3390/socsci12080465.
Abstract:
The use of TikTok is more widespread now than ever, and it has a big impact on users’ daily lives, with self-perceived identity and personal values being topics of interest in light of the algorithmically curated content. This mini-review summarizes current findings related to the TikTok algorithm, and the impact it has on self-perceived identity, personal values, or related concepts of the Self. We pass through the contents of algorithmic literacy and emphasize its importance along with users’ attitudes toward algorithms. In the first part of our results, we show conceptual models of algorithms like the crystal framework, platform spirit, and collective imaginaries. In the second part, we talk about the degree of impact a social media algorithm may exert over an individual’s sense of self, understanding how the algorithmized self and domesticated algorithm are trying to sum up the dual development of this relationship. In the end, with the concept of Personal Engagement and the role of cognitive biases, we summarize the current findings and discuss the questions that still need to be addressed. Performing research on the topic of social media, especially TikTok, poses ethical, cultural, and regulatory challenges for researchers. That is why we will discuss the main theoretical frameworks that were published with their attached current studies and their impact on the current theoretical models as well as the limitations within these studies. Finally, we discuss further topics of interest related to the subject and possible perspectives, as well as recommendations regarding future research in areas like impact on personal values and identity, cognitive biases, and algorithmic literacy.
Dissertations / Theses on the topic "Algorithme cognitif":
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Calandra, Joséphine. "L'algorithmie cognitive et ses applications musicales." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUL148.
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Cette thèse présente la formalisation et le développement d’un logiciel d'analyse musicale appelé "Multiscale Oracle Representations For Organized Sounds" (MORFOS). Ce logiciel vise à mettre en œuvre un modèle multi-échelle de la forme musicale basé sur l’Algorithme Cognitif de Jean-Marc Chouvel. Les travaux de cette thèse s'inscrivent dans la continuité de l'analyse cognitive en musicologie, visant à comprendre les processus cognitifs qui interviennent lors de l'écoute musicale. Nous étudions une représentation hiérarchisée de la musique et explorons l’influence de cette hiérarchisation dans l’organisation des événements musicaux dans le temps et la compréhension de la musique. Nous formalisons ainsi les concepts de matériau, d’objet et de diagramme formel, et nous introduisons le Diagramme Formel Multi-échelle qui décrit la structure musicale à différentes échelles temporelles et niveaux d'analyse. Celui-ci est composé de trois plans que nous introduisons : la forme, la structure et l’organisation. L'implémentation informatique de MORFOS a été réalisée en Python et accepte des représentations audio, symboliques ou vectorielles. Ce logiciel présente une architecture modulaire intégrant différents modules de traitement audio, de classification et de segmentation : nous présentons ainsi différentes mesures implémentées sous forme d’un ensemble de règles et discutons des contraintes associées à l’étude de la classification et de la segmentation à partir d’une représentation audio. Nous présentons ainsi la notion d’Agenda, qui correspond au choix par l’utilisateur d’un ensemble de règles permettant de représenter un modèle « d’écoute » pour l’analyse d’une œuvre musicale par le logiciel. La thèse explore également la question de la complexité de la structure musicale : nous proposons l’expression d’un coût associé à la description de l’objet musical acquis en fonction de son contexte, selon la définition de Kolmogorov. Nous cherchons également à comparer le comportement du logiciel MORFOS avec les phénomènes d'attention et la charge cognitive lors de l'écoute musicale. Une expérience visant à mesurer la charge cognitive pendant la tâche de segmentation musicale a ainsi été conçue. Cette thèse présente par ailleurs des réflexions sur la visualisation des diagrammes formels multi-échelles. A cette occasion, nous avons développé une interface permettant de rendre le logiciel accessible à tous les utilisateurs. Enfin, des exemples d'analyses musicales réalisées avec MORFOS sont présentées, sur une base de données musicales pop ainsi qu’un corpus d'œuvres classiquesThis thesis presents the formalization and development of a music analysis software called "Multiscale Oracle Representations For Organized Sounds" (MORFOS). This software aims to implement a multi-scale model of musical form based on Jean-Marc Chouvel's Cognitive Algorithm. The work in this thesis is part of the cognitive analysis in musicology, aimed at understanding the cognitive processes involved in listening to music. We study a hierarchical representation of music and explore the influence of this hierarchy on the organization of musical events over time and on musical comprehension. We formalize the concepts of material, object, and formal diagram, and introduce the Multi-scale Formal Diagram, which describes musical structure at different temporal scales and levels of analysis. This comprises three planes, which we introduce: form, structure, and organization. MORFOS has been implemented in Python and accepts audio, symbolic, and vector representations. This software features a modular architecture integrating different modules for audio processing, classification, and segmentation: we present different measures implemented in the form of a set of rules and discuss the constraints associated with the study of classification and segmentation based on an audio representation. We also introduce the notion of Agenda, which corresponds to the user's choice of a set of rules to represent a "listening" model for the software's analysis of a musical work. The thesis also explores the question of the complexity of the musical structure: we propose the expression of a cost associated with the description of the acquired musical object depending on its context, according to Kolmogorov's definition. We also seek to compare the behavior of MORFOS software with attentional phenomena and cognitive load during musical listening. An experiment designed to measure cognitive load during the musical segmentation task has thus been devised. This thesis also presents reflections on the visualization of multi-scale formal diagrams. To this end, we have developed an interface to make the software accessible to all users. Finally, examples of musical analyses carried out with MORFOS are presented, on a pop music database and a corpus of classical works
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Li, Jun. "Genetic Granular Cognitive Fuzzy Neural Networks and Human Brains for Comparative Cognition." Digital Archive @ GSU, 2005. http://digitalarchive.gsu.edu/cs_theses/7.
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In this thesis, Genetic Granular Cognitive Fuzzy Neural Networks (GGCFNN), combining genetic algorithms (GA) and granular cognitive fuzzy neural networks (GCFNN), is proposed for pattern recognition problems. According to cognitive patterns, biological neural networks in the human brain can recognize different patterns. Since GA and neural networks represent two learning methods based on biological science, it is indispensable and valuable to investigate how biological neural networks and artificial neural networks recognize different patterns. The new GGCFNN, based on granular computing, soft computing and cognitive science, is used in the pattern recognition problems. The hybrid forward-wave-backward-wave learning algorithm, as a main learning technology in GCFNN, is used to enhance learning quality. GA optimizes parameters to make GGCFNN get better learning results. Both pattern recognition results generated by human persons and those by GGCFNN are analyzed in terms of computer science and cognitive science.
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Ginhac, Dominique. "Adéquation Algorithme architecture : Aspects logiciels, matériels et cognitifs." Habilitation à diriger des recherches, Université de Bourgogne, 2008. http://tel.archives-ouvertes.fr/tel-00646480.
Abstract:
Les travaux présentés dans le cadre de cette Habilitation à Diriger des Recherches s'inscrivent principalement dans la problématique dite d'" Adéquation Algorithme Architecture ". Ils ont pour objectif commun la mise en œuvre de systèmes matériels et logiciels dédiés à la vision artificielle à fortes contraintes temporelles. Ils se focalisent sur différents aspects cruciaux tels que l'acquisition d'images par des capteurs dédiés, le développement et la programmation d'architectures optimisées de traitement des images et l'implantation d'algorithmes de traitement du signal et d'images en temps réel sur ces architectures.
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El-Nainay, Mustafa Y. "Island Genetic Algorithm-based Cognitive Networks." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28297.
Abstract:
The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed reasoning and learning across the protocol stack and throughout the network. Various cognitive node and cognitive network architectures with different levels of maturity have been proposed in the literature. All of them adopt the idea of coupling network devices with sensors to sense network conditions, artificial intelligence algorithms to solve problems, and a reconfigurable platform to apply solutions. However, little further research has investigated suitable reasoning and learning algorithms.
In this dissertation, we take cognitive network research a step further by investigating the reasoning component of cognitive networks. In a deviation from previous suggestions, we suggest the use of a single flexible distributed reasoning algorithm for cognitive networks. We first propose an architecture for a cognitive node in a cognitive network that is general enough to apply to future networking challenges. We then introduce and justify our choice of the island genetic algorithm (iGA) as the distributed reasoning algorithm.
Having introduced our cognitive node architecture, we then focus on the applicability of the island genetic algorithm as a single reasoning algorithm for cognitive networks. Our approach is to apply the island genetic algorithm to different single and cross layer communication and networking problems and to evaluate its performance through simulation. A proof of concept cognitive network is implemented to understand the implementation challenges and assess the island genetic algorithm performance in a real network environment. We apply the island genetic algorithm to three problems: channel allocation, joint power and channel allocation, and flow routing. The channel allocation problem is a major challenge for dynamic spectrum access which, in turn, has been the focal application for cognitive radios and cognitive networks. The other problems are examples of hard cross layer problems.
We first apply the standard island genetic algorithm to a channel allocation problem formulated for the dynamic spectrum cognitive network environment. We also describe the details for implementing a cognitive network prototype using the universal software radio peripheral integrated with our extended implementation of the GNU radio software package and our island genetic algorithm implementation for the dynamic spectrum channel allocation problem. We then develop a localized variation of the island genetic algorithm, denoted LiGA, that allows the standard island genetic algorithm to scale and apply it to the joint power and channel allocation problem. In this context, we also investigate the importance of power control for cognitive networks and study the effect of non-cooperative behavior on the performance of the LiGA.
The localized variation of the island genetic algorithm, LiGA, is powerful in solving node-centric problems and problems that requires only limited knowledge about network status. However, not every communication and networking problems can be solved efficiently in localized fashion. Thus, we propose a generalized version of the LiGA, namely the K-hop island genetic algorithm, as our final distributed reasoning algorithm proposal for cognitive networks. The K-hop island genetic algorithm is a promising algorithm to solve a large class of communication and networking problems with controllable cooperation and migration scope that allows for a tradeoff between performance and cost. We apply it to a flow routing problem that includes both power control and channel allocation. For all problems simulation results are provided to quantify the performance of the island genetic algorithm variation. In most cases, simulation and experimental results reveal promising performance for the island genetic algorithm.
We conclude our work with a discussion of the shortcomings of island genetic algorithms without guidance from a learning mechanism and propose the incorporation of two learning processes into the cognitive node architecture to solve slow convergence and manual configuration problems. We suggest the cultural algorithm framework and reinforcement learning techniques as candidate leaning techniques for implementing the learning processes. However, further investigation and implementation is left as future work.Ph. D.
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Butterfield, Aaron S. "Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979.
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Béler, Cédrick. "Modélisation générique d'un retour d'expérience cognitif : application à la prévention des risques." Phd thesis, Toulouse, INPT, 2008. http://oatao.univ-toulouse.fr/7249/1/beler.pdf.
Abstract:
Nous avons défini dans cette thèse une architecture logicielle générique permettant de réaliser des applications de retour d'expérience cognitif. Ces derniers intègrent une formalisation de l'analyse experte et sont une alternative aux Systèmes à Bases de Connaissance. Les applications sont opérationnalisées à partir de la définition du modèle de l'expérience qui est basé sur une structure objet simple couplée avec le modèle des croyances transférables pour prendre en compte les intertitudes. Nous avons développé des algorithmes génériques de recherche adaptés à la formalisation retenue de l'entité expérience ainsi qu'un alogorithme d'extraction d'un indicateur du risque. Ces algorithmes sont basés sur une proposition de similarité ensembliste particulière. Le modèle générique est basé sur un modèle adaptatif (Adaptive Object Model). Nous avons appliqué une partie des résultats de la thèse dans le cadre d'un projet Européen INTERREG SUP (Sécurité Urgence Pyrénées).
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Mäkeläinen, M. (Marko). "Algorithms for opportunistic load balancing cognitive engine." Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201303011071.
Abstract:
Due to the increasing use of more and more powerful smart devices demands on the scarce radio spectrum are becoming more intense. One way to cope with increasing demands on radio spectrum is to apply innovative and flexible authorization schemes like spectrum sharing. Under the spectrum sharing paradigm, multiple users and/or systems are authorized to utilize the same spectrum band in a defined sharing agreement. A technology that is generally recommended for the implementation of spectrum sharing is called cognitive radio (CR). In this thesis, we design and implement a cognitive engine (CE) that intelligently and dynamically allocates spectrum resources to users. We first consider a scenario where a network has an exclusive access to a spectrum band and the CE accepts or rejects the arrival user requests based on an algorithm that takes into account a user’s priority and its bandwidth demand. We then consider a spectrum sharing scenario where along with the exclusive utilization to its own spectrum band a network also can opportunistically utilize another network’s spectrum band. For this scenario, we design and implement a CE that performs two main tasks: 1) Accepts or rejects arrival user requests based on a priority based algorithm; and 2) it intelligently load balances the user traffic between the two available network resources, while taking into account the primary user activity in the shared spectrum band. We provide a load balancing algorithm and evaluate its performance under different primary and secondary user traffic scenarios. We show that the proposed load balancing algorithm increases average throughput of the network and it also reduces the average number of users rejected by the networkYhä tehokkaampien älykkäiden langattomien päätelaitteiden nopea lisääntyminen johtaa niukan radiospektrin yhä kiihtyvään käyttöön. Eräs menetelmä radiospektrin lisääntyvän kysynnän tyydyttämiseen on hyödyntää innovatiivista ja joustavaa resurssin käytönjakoa kuten spektrin jakamista. Spektrinjakamismalli mahdollistaa useiden käyttäjien ja/tai järjestelmien yhtäaikaisen käytön samalla taajuuskaistalla hyödyntämällä sovittua käytäntöä resurssien jakamisesta. Radiospektrin jakaminen on tänä päivänä yleisesti suositeltu toteuttamaan hyödyntämällä kognitiivista radioteknologiaa. Tässä työssä suunnittellaan ja toteutetaan kognitiivinen päätöksentekokone, joka jakaa radiospektriresursseja käyttäjille älykkäästi ja dynaamisesti. Kognitiivista päätöksentekokonetta radioresurssien jakamisessa hyödynnetään kahdessa skenaariossa. Ensimmäisessä skenaariossa radioverkolla on yksinomainen pääsy taajuuskaistalle, jonka käyttöä kognitiivinen päätöksentekokone säätelee joko hyväksymällä tai hylkäämällä verkkoon liittyviä käyttäjiä. Kognitiivinen päätöksentekokoneen päätökset perustuu algoritmiin, joka ottaa huomioon käyttäjien määritetyn tärkeyden ja käyttäjän vaatiman kaistanleveyden. Seuraavassa skenaariossa radioverkko voi oman yksinomaisen taajuuskaistan lisäksi hyödyntää opportunisesti toisen radioverkon taajuuskaistaa silloin, kun siellä ei ole liikennettä. Tätä skenaariota varten suunnitteltiin kognitiivinen päätöksentekokone, jolla on kaksi päätehtävää: 1) hyväksyä tai hylätä verkkoon liittyviä käyttäjiä edellämainitun tärkeysperusteisen algoritmin avulla; ja 2) jakaa käyttäjien liikennettä kahden tarjolla olevan verkon välillä samalla ottaen huomioon opportunistisen resurssin pääkäyttäjien liikenteen jaetulla taajuuskaistalla. Tässä työssä esitellään toteutettu kuormantasausalgoritmi, jonka suorituskykyä tarkastellaan erilaisissa pääkäyttäjien ja toissijaisien käyttäjien liikenneskenaarioissa. Simulaatiotulokset osoittavat, että esitellyn kuormanjakoalgoritmin hyödyntäminen kognitiivisessa päätöksentekokoneessa parantaa verkon keskimääräistä siirtonopeutta, sekä vähentää keskimääräistä käyttäjien hylkäysastetta verkossa. Algoritmimme parantaa opportunistisen taajuuskaistan käyttöastetta. Algoritmimme ottaa myös huomioon käyttäjille asetetut prioriteetit ja parantaa korkeampi prioriteettisten käyttäjien asemaa verkossa. Tämä tulee ilmi muun muassa korkeampi prioriteettisten käyttäjien pienemmässä hylkäysasteessa
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Mariani, Andrea <1984>. "Spectrum Sensing Algorithms for Cognitive Radio Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5615/2/Mariani_Andrea_SpectrumSensingforCognitiveRadio.pdf.
Abstract:
Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission.
In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.
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Mariani, Andrea <1984>. "Spectrum Sensing Algorithms for Cognitive Radio Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5615/.
Abstract:
Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission.
In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.
10
Reje, Franzén Fanny, and Saga Gardelin. "Hide and seek with algorithm : En intervjustudie av cosplay-kreatörers "folk" teorier i förhållande till TikToks algoritm." Thesis, Linnéuniversitetet, Institutionen för medier och journalistik (MJ), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104833.
Abstract:
This essay aims to study the relationship between cosplay content creators and TikTok’s algorithm. To study this relationship the essay will conduct a qualitative semi-structured interviews with creators from the cosplay community on TikTok. Since the rise of digital plattforms the media and the role of producer as well as consumer has changed drastically. TikTok has been growing rapidly in popularity since its entry on the market, and by 2020 it had 500 million active users. Since many of today's digital platforms have consumer produced content, the consumer of today has taken on a mixed role between consuming and creating content, which creates a new relationship. The content consumers produce vary vastly on TikTok but one kind that has been present in much of TikTok’s existence is cosplay content. Cosplayers are creators who design costumes to already established characters or franchises. Since a discourse has started in the cosplay community on TikTok about the algorithm suppressing their content the study found it to be a good way to start examining content creators as individuals and how they behave towards an algorithm in their content creation process. The study aims to use algorithmic “folk” theory to examine what theories have been created in the community and how the theories affect the creators. The study also applies gatekeeping theory and social cognitive theory (SCT) to paint a clearer picture in how these creators view the algorithm. Seven interviews with cosplay content creators were conducted and with the help of a thematic analysis method the study found several themes in how the creators view and behave in relation to TikTok and its algorithm. The results of our study shows that there’s a definite present of “folk” theories created inside of the community. The most distinct behaviour relating to “folk” theory among the creators was that they can’t use the hashtag cosplay in the belief that the algorithm would suppress the content. This study concludes that the creators are more aware of the algorithm then they themself know and have different ways of working with and around it.
Books on the topic "Algorithme cognitif":
1
Foster, C. L. Algorithms, abstraction, and implementation: Levels of detail in cognitive science. London: Academic Press, 1992.
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Perlovsky, Leonid, Ross Deming, and Roman Ilin. Emotional Cognitive Neural Algorithms with Engineering Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22830-8.
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Robbins, Trevor W., Peter M. Todd, and Thomas Trenholm Hills. Cognitive search: Evolution, algorithms, and the brain. Cambridge, MA: MIT Press, 2012.
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Esposito, Anna, Amir Hussain, Maria Marinaro, and Raffaele Martone, eds. Multimodal Signals: Cognitive and Algorithmic Issues. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00525-1.
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Pinna, Simone. Extended Cognition and the Dynamics of Algorithmic Skills. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51841-1.
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Talvitie, Vesa. Freudian unconscious and cognitive neuroscience: From unconscious fantasies to neural algorithms. London: Karnac, 2009.
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Talvitie, Vesa. Freudian unconscious and cognitive neuroscience: From unconscious fantasies to neural algorithms. London: Karnac, 2009.
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Perlovsky, Leonid. Emotional Cognitive Neural Algorithms with Engineering Applications: Dynamic Logic: FromVague to Crisp. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.
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Günthner, W. Enhancing cognitive assistance systems with inertial measurement units. Berlin: Springer, 2008.
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Esposito, Anna. Multimodal signals: Cognitive and algorithmic issues : COST Action 2102 and euCognition International School Vietri Sul Mare, Italy, April 21-26, 2008 : revised selected and invited papers. Berlin: Springer, 2009.
Book chapters on the topic "Algorithme cognitif":
1
Hausser, Roland. "Algorithm." In Computational Cognition, 21–36. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37499-9_2.
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Frühwirth, Thom, and Slim Abdennadher. "Algorithm = Logic + Control." In Cognitive Technologies, 7–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05138-2_2.
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Kaur, Kiranjit, and Vijay Laxmi. "A Novel Method of Data Partitioning Using Genetic Algorithm Work Load Driven Approach Utilizing Machine Learning." In Cognitive Computing in Human Cognition, 49–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48118-6_5.
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Der, Ralf, and Georg Martius. "Algorithmic Implementation." In Cognitive Systems Monographs, 261–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20253-7_15.
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Kaindl, H. "Tree Searching Algorithms." In Computers, Chess, and Cognition, 133–58. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-9080-0_8.
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Leiser, David, and Christiane Gillièron. "The Extraction Algorithm beneath the Basic Algorithm." In Cognitive Science and Genetic Epistemology, 79–97. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-5649-3_5.
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Fetzer, James H. "Mental Algorithms." In Computers and Cognition: Why Minds are not Machines, 101–29. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0973-7_5.
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Conrardy, Céline, Roland de Guio, and Bruno Zuber. "Facetwise Study of Modelling Activities in the Algorithm for Inventive Problem Solving ARIZ and Evolutionary Algorithms." In Design Computing and Cognition ’10, 189–207. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0510-4_11.
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Palestro, James J., Per B. Sederberg, Adam F. Osth, Trisha Van Zandt, and Brandon M. Turner. "Likelihood-Free Algorithms." In Likelihood-Free Methods for Cognitive Science, 13–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72425-6_2.
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Zenil, Hector, Fernando Soler Toscano, and Nicolas Gauvrit. "Algorithmic Complexity in Cognition." In Methods and Applications of Algorithmic Complexity, 191–256. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64985-5_9.
Conference papers on the topic "Algorithme cognitif":
1
Carpenter, Steven, Xinming Yu, Melih Altun, James Graham, J. Jim Zhu, and Janusz Starzyk. "Vision Guided Motion Control of a Biomimetic Quadruped Robot: RoboCat." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-63805.
Abstract:
This paper presents the vision system and visual processing for a biomimetic elastic cable-driven quadruped robot—RoboCat. The paper is geared towards selection of appropriate visual servoing techniques for RoboCat such as vision algorithms, high-level cognition algorithms, software architecture and hardware implementation. The system uses two video cameras for stereo vision data acquisition and a SUMIT-ism form factor embedded computer for vision data processing. The vision system employs a color based target recognition algorithm, a neural network based shape recognition algorithm and a Color and Zernike moment based face detection algorithm. The paper presents the vision algorithms, vision guidance and motion tracking algorithms, rule-based decision making algorithms and the open architecture of the autonomous vision tracking system. Experimental testing results (including video clips) are also presented.
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Huang, Shan, Haiyan Wang, Chengqi Xue, and Shuang Xia. "Icon Similarity Algorithm Based on Skeleton Comparison." In Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100963.
Abstract:
Icon plays a crucial role in infographics, which additionally carries essential functions in the human-computer graphical user interface (GUI). However, too similar icon is easy to trigger confusion in the process of using. In this paper, we explored the use of the cognitive rules from global to local based on the theory of topological perception and built a computational discrimination tool from the human perception to describe similarity. Screening out icons that are too similar is the primary purpose of this research to avoid errors in use. We utilized the skeleton algorithm to extract the global features of icons. The optimal subsequence bijection and Hungarian algorithm were used to compare the global skeleton of the icon. Accordingly, the similarity between the icons was calculated. To verify the proposed algorithm, we conducted a subjective cognitive experiment. Participants were asked to rank the similarity of the experimental materials and compare the results with the calculation outcomes. Results demonstrate that the proposed calculation methodology based on skeleton comparison is close to subjective cognition, which can effectively describe the human perception of icon similarity.
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Amanna, Ashwin, Matthew J. Price, Soumava Bera, Manik Gadhiok, and Jeffrey H. Reed. "Cognitive Engine Architecture for Railway Communications." In ASME 2010 Rail Transportation Division Fall Technical Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/rtdf2010-42011.
Abstract:
This paper discusses a railway specific cognitive radio that builds upon software defined radio (SDR) platforms to adapt the radio based situational awareness. Cognitive Radio incorporates artificial intelligence based algorithms with reconfigurable software-defined radios that enable automatic adjustments of the radio to improve performance and overcome obstacles the radio may confront in the field (i.e. environmental/man-made interference, occupying the same channel as a user with higher priority, etc.). This paper describes the Railway Cognitive Radio (Rail-CR) architecture and illustrates preliminary results in simulation. The proposed cognitive engine architecture consists of a case-based reasoned (CBR) and a Genetic Algorithm (GA) optimization routine. This paper discusses the overall cognitive architecture, the relationship between the CBR and the GA based on weighted objective functions, and metrics for assessing performance. Methods for case representation, quantifying similarity between cases histories, and techniques for managing case growth rate are presented as well as a proposed test bed SDR platform.
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Gilg, Marc, Yaser Yousef, and Pascal Lorenz. "Using Image Processing Algorithms for Energy Efficient Routing Algorithm in Sensor Networks." In 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns (COMPUTATIONWORLD). IEEE, 2009. http://dx.doi.org/10.1109/computationworld.2009.98.
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Guo, Yan, and Ning Li. "Cognitive beamforming algorithm." In 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6057249.
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Saidala, Ravi Kumar, and Nagaraju Devarakonda. "The tornadogenesis optimization algorithm." In 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2017. http://dx.doi.org/10.1109/icci-cc.2017.8109777.
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Teng, Zhiqiang, Haodong Chen, Qitao Hou, Wanbing Song, Chenchen Gu, and Ping Zhao. "Design of a Cognitive Rehabilitation System Based on Gesture Recognition." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23579.
Abstract:
Abstract Computer-assisted cognitive training is an effective intervention for patients with mild cognitive impairment (MCI), which can avoid the disadvantages of traditional cognitive training that consumes a lot of medical resources and is difficult to be standardized. However, many computer-assisted cognitive training systems have unfriendly human-computer interaction, for not considering that most MCI patients have certain difficulties in using computers. In this paper, we design a cognitive training system which allows patients to implement human-computer interaction through gestures. First, a gesture recognition algorithm is proposed, in which we implement gesture segmentation based on YCbCr color space and Otsu algorithm, extract Fourier Descriptors of gesture contour as feature vectors and use SVM algorithm to train a classifier to recognize gestures. Then, the graphical user interface (GUI) of the system is designed to realize the task requirement of cognitive training for the MCI patients. Finally, the results of tests show the accuracy of the algorithm and the feasibility of the GUI. With the above computer-assisted cognitive training system, patients can achieve human-computer interaction only through gestures without the need to use keyboard, mouse, etc., greatly reducing the burden of patients during training.
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Paul, Padma Polash, and Marina Gavrilova. "Novel multimodal template generation algorithm." In 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2013. http://dx.doi.org/10.1109/icci-cc.2013.6622228.
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Ren, Qingchun, and Qilian Liang. "Performance Analysis of Energy Detection for Cognitive RadioWireless Networks." In 2007 International Conference on Wireless Algorithms, Systems and Applications. IEEE, 2007. http://dx.doi.org/10.1109/wasa.2007.17.
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Abbass, Hussein. "On the Role of Modelling and Simulation for Artificial Intelligence." In 36th ECMS International Conference on Modelling and Simulation. ECMS, 2022. http://dx.doi.org/10.7148/2022-0005.
Abstract:
Artificial Intelligence (AI) is the ubiquitous revolutionary technology of this century. AI has revolutionised humanity, including industry and government organisations, and transformed our world into smart digital spaces. As a discipline, one of the definitions of AI is the automation of cognition; or, put simply, the set of technologies required to support the design and implementation of artificial cognition in artificial systems. To design an intelligent system/machine, technologists need to transform the algorithms of AI into a system-of-systems design of cognition, whereby the artificial agent can sense, make sense, make decisions, take decisions, and learn about the contexts it is situated within. Modelling and Simulation (M&S) sit at the core of an artificial agent’s design and implementation components. In this presentation, I will cover the use of M&S within AI from different angles . In doing so, I will bring elements from my research to showcase how M&S not only contributes to AI but also shows that without M&S, AI can’t operate. I will paint futures that range from very concrete and narrowly defined uses of AI to a world of human and artificial cognitive agents. Humans educate AI agents, and AI agents educate humans. I will then conclude with some challenges for the M&S community to support the effort in advancing AI. This presentation will be drawn from many of my published works; below are some critical references for interested readers.
Reports on the topic "Algorithme cognitif":
1
Perlovsky, Leonid I. Cognitive Algorithms for Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, March 2011. http://dx.doi.org/10.21236/ada546287.
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Anandkumar, Animashree, Nithin Michael, Ao K. Tang, and Ananthram Swami. Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada524660.
3
Oleksiuk, Vasyl P., and Olesia R. Oleksiuk. Exploring the potential of augmented reality for teaching school computer science. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4404.
Abstract:
The article analyzes the phenomenon of augmented reality (AR) in education. AR is a new technology that complements the real world with the help of computer data. Such content is tied to specific locations or activities. Over the last few years, AR applications have become available on mobile devices. AR becomes available in the media (news, entertainment, sports). It is starting to enter other areas of life (such as e-commerce, travel, marketing). But education has the biggest impact on AR. Based on the analysis of scientific publications, the authors explored the possibilities of using augmented reality in education. They identified means of augmented reality for teaching computer science at school. Such programs and services allow students to observe the operation of computer systems when changing their parameters. Students can also modify computer hardware for augmented reality objects and visualize algorithms and data processes. The article describes the content of author training for practicing teachers. At this event, some applications for training in AR technology were considered. The possibilities of working with augmented reality objects in computer science training are singled out. It is shown that the use of augmented reality provides an opportunity to increase the realism of research; provides emotional and cognitive experience. This all contributes to engaging students in systematic learning; creates new opportunities for collaborative learning, develops new representations of real objects.
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olesia O. Prokofieva, Olha V. Kovalova, and Arnold E. Kiv. Features of implementation of modern AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4413.
Abstract:
The article deals with the actual issue of the specificity and algorithm of the introduction of innovative AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders (ASD). An innovative element of theoretical and methodological analysis of the problem and empirical research is the detection of vectors of a constructive combination of traditional psycho-correctional and psycho-diagnostic approaches with modern AR technologies. The analysis of publications on the role and possibilities of using AR technologies in the process of support children with ASD (autism spectrum disorder) and inclusive environment was generally conducted by surfing on the Internet platforms containing the theoretical bases for data publications of scientific journals and patents. The article also analyzes the priorities and potential outcomes of using AR technologies in psycho-correction and educational work with autistic children. According to the results of the analysis of scientific researches, Unified clinical protocol of primary, secondary (specialized), tertiary (highly specialized) medical care and medical rehabilitation “Autism spectrum disorders (disorders of general development)”, approaches for correction, development and education of children with ASD, AR technologies were selected for further implementation in a comprehensive program of psychological and pedagogical support for children with ASD. The purpose of the empirical study is the search, analysis and implementation of multifunctional AR technologies in the psycho-correctional construct of psychological and pedagogical support of children with ASD. According to the results of the pilot study, the priorities and effectiveness of using AR technologies in the development of communicative, cognitive, emotional-volitional, mnemonic abilities of children and actualization of adaptive potential and adaptive, socially accepted behaviors are made. The possibilities and perspectives of using AR technologies as an element of inclusive environment, with regard to nosology and phenomenology, need further investigation.
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Petrovych, Olha B., Alla P. Vinnichuk, Viktor P. Krupka, Iryna A. Zelenenka, and Andrei V. Voznyak. The usage of augmented reality technologies in professional training of future teachers of Ukrainian language and literature. CEUR Workshop Proceedings, July 2021. http://dx.doi.org/10.31812/123456789/4635.
Abstract:
The article deals with the peculiarities of creation and practical application of augmented reality (AR) technologies for the organization of students-philologists’ individual and group work in studying the discipline “Methodic of teaching literature”. The relevance of the introduction of AR technologies for the future teachers-philologists’ readiness formation to the professional activity is substantiated. Analysis of the scientific sources suggested that the professional training process requires the modernization of teaching methods, and the usage of information and communication technologies (ICT) in education, in particular AR technologies, allows to make the learning process interesting and exciting. The domestic and foreign experience of AR technologies application into current educational practices is generalized. A step-by-step algorithm for creating the AR in the mobile application Unite and its subsequent content filling for professional training of future teachers of Ukrainian language and literature is described. The visualization of the educational content of the lepbook “Incredible Lesya Ukrainka”, made by students- philologists at the Mykhailo Stelmakh Faculty of Philology and Journalism of Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University during the studying the discipline “Methodic of teaching literature”, is detailed. It is specified that the educational process is based on the creation AR with the visualization of interactive learning materials with animation, instructions, links, video content, illustrations etc. according to the rubrics of the lepbook. It is emphasized that the implementation of AR technologies provides the increasing of motivation for systematic mastering of practical skills, enhances students’ concentration and attention, increases their cognitive experience, promotes the development of their creative abilities, produces the opportunities of using the visualized content for students’ research work, stimulates them to self-expression, motivates them to self-development, trains them to the skillful use of the Internet, modern gadgets and mobile applications, etc. Prospects for studying the possibilities of using AR technologies in lessons of Ukrainian literature at secondary school are determined.
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olha V. Kovalova, Valentyna V. Voloshyna, Oleksii V. Sysoiev, and Mariya P. Shyshkina. The use of augmented reality technologies in the development of emotional intelligence of future specialists of socionomic professions under the conditions of adaptive learning. CEUR Workshop Proceedings, July 2020. http://dx.doi.org/10.31812/123456789/4633.
Abstract:
In modern conditions, innovative augmented reality technologies are actively developing, which are widespread in many areas of human activity. Introduction of advanced developments in the process of professional training of future specialists of socionomic professions in the conditions of adaptive training, contributes to the implementation of the principles of a personalized approach and increase the overall level of competitiveness. The relevant scientific article is devoted to the theoretical and empirical analysis result of conducting a psychodiagnostic study on an innovative computer complex HC-psychotest. of the features of the implementation of augmented reality technologies in the construct of traditional psychological and pedagogical support aimed at the development of emotional intelligence of the future specialist. The interdisciplinary approach was used while carrying out the research work at the expense of the general fund of the state budget: “Adaptive system for individualization and personalization of professional training of future specialists in the conditions of blended learning”. A comprehensive study of the implementation of traditional psychological-pedagogical and innovative augmented reality technologies was conducted in the framework of scientific cooperation of STEAM-Laboratory, Laboratory of Psychophysiological Research and Laboratory of Psychology of Health in Bogdan Khmelnitsky Melitopol State Pedagogical University. The theoretical analysis considers the structural model of emotional intelligence of the future specialist of socionomic professions, which is represented by two structural components: intrapersonal construct of emotional intelligence and interpersonal construct of emotional intelligence. Each component mediates the inherent emotional intelligence of interpretive, regulatory, adaptive, stress-protective and activating functions. The algorithm of the empirical block of research is presented by two stages: ascertaining and forming research. According to the results of the statement, low indicators were found on most scales, reflecting the general level of emotional intelligence development of future specialists, actualizing the need to find and implement effective measures for the development of emotional intelligence components in modern higher education and taking into account information development and digitalization. As part of the formative stage of the research implementation, a comprehensive program “Development of emotional intelligence of future professionals” was tested, which integrated traditional psychological and pedagogical technologies and innovative augmented reality technologies. This program is designed for 24 hours, 6 thematic classes of 4 hours. According to the results of a comprehensive ascertaining and shaping research, the effectiveness of the influence of augmented reality technologies on the general index of emotional intelligence is proved. The step-by-step model of integration of augmented reality components influencing the ability to analyze, understand and regulate emotional states into a complex program of emotional intelligence development is demonstrated. According to the results of the formative study, there is a dominance of high indicators of the following components: intrapersonal (50%), interpersonal (53.3%). Thus, we can say that intrapersonal and interpersonal emotional intelligence together involve the actualization of various cognitive processes and skills, and are related to each other. Empirical data were obtained as a