Academic literature on the topic 'Algorithmic'

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Journal articles on the topic "Algorithmic"

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Bender, Sarah. "Algorithmic Elections." Michigan Law Review, no. 121.3 (2022): 489. http://dx.doi.org/10.36644/mlr.121.3.algorithmic.

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Artificial intelligence (AI) has entered election administration. Across the country, election officials are beginning to use AI systems to purge voter records, verify mail-in ballots, and draw district lines. Already, these technologies are having a profound effect on voting rights and democratic processes. However, they have received relatively little attention from AI experts, advocates, and policymakers. Scholars have sounded the alarm on a variety of “algorithmic harms” resulting from AI’s use in the criminal justice system, employment, healthcare, and other civil rights domains. Many of
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Yushchenko, E. L., and G. E. Tseitlin. "Issues of algorithmics and glushkov’s systems of algorithmic algebras." Cybernetics and Systems Analysis 34, no. 4 (1998): 532–39. http://dx.doi.org/10.1007/bf02666997.

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Röhl, Tobias, and Matthias Kirchner. "Algorithmische Alchemie – die sozio-technische Reproduktion sozialer Ungleichheit im Bildungssystem." Soziale Probleme 34, no. 2 (2023): 273–89. https://doi.org/10.5281/zenodo.13832371.

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Algorithmische Systeme versprechen, die Bewertung schulischer Leistung zu objektivieren und Bildungsangebote zu individualisieren. Statt subjektiver Urteile von Lehrpersonen sollen Algorithmen entscheiden, wie Freitextaufgaben und Essays zu bewerten sind und wie Aufgaben zugeteilt werden. Doch die Intransparenz der Technik erzeugt unbemerkt neue Formen der Ungleichheit. Die Datens&auml;tze und ihre algorithmische Auswertung unterliegen einem <em>algorithmic bias, </em>der bestehende Bildungsungleichheiten nicht bloss reproduziert, sondern sogar verst&auml;rkt. Wir diskutieren diesen Umstand an
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Bishop, Sophie. "Algorithmic Experts: Selling Algorithmic Lore on YouTube." Social Media + Society 6, no. 1 (2020): 205630511989732. http://dx.doi.org/10.1177/2056305119897323.

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This article considers the growing influence of self-styled algorithmic “experts.” Experts build valuable brands, accumulate notoriety, and piece together careers by selling theorizations of algorithmic visibility on YouTube to aspiring and established creators. They function as intermediaries between sanctioned YouTube industries and the agency of cultural producers. Expertise is developed through research, strategies, and theories to help content creators mitigate platform-specific risks, particularly the risk of algorithmic invisibility. Experts develop entrepreneurial self-brands and posit
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Gal, Michal. "Algorithmic Challenges to Autonomous Choice." Michigan Technology Law Review, no. 25.1 (2018): 59. http://dx.doi.org/10.36645/mtlr.25.1.algorithmic.

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We then explore how autonomous algorithmic assistants affect the legal framework. Some issues challenge the very use of algorithmic assistants: Should the law place an age limit on the use of such algorithms? Should legal limits be placed on their use in certain spheres? Other issues arise from the construction of preferences by algorithms. To wit, in a market in which demand is driven by algorithms, can we necessarily regard the choices made as expressions of user preferences that serve our socio-political goals? Even if the answer is positive—does this new mode of user choice fit current leg
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Fowler, John W. "Algorithmic Composition." Computer Music Journal 18, no. 3 (1994): 8. http://dx.doi.org/10.2307/3681175.

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Monahan, Torin. "Algorithmic Fetishism." Surveillance & Society 16, no. 1 (2018): 1–5. http://dx.doi.org/10.24908/ss.v16i1.10827.

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Surveillance-infused forms of algorithmic discrimination are beginning to capture public and scholarly attention. While this is an encouraging development, this editorial questions the parameters of this emerging discussion and cautions against algorithmic fetishism. I characterize algorithmic fetishism as the pleasurable pursuit of opening the black box, discovering the code hidden inside, exploring its beauty and flaws, and explicating its intricacies. It is a technophilic desire for arcane knowledge that can never be grasped completely, so it continually lures one forward into technical rea
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DuBrin, Rosie, and Ashley E. Gorham. "Algorithmic interpellation." Constellations 28, no. 2 (2021): 176–91. http://dx.doi.org/10.1111/1467-8675.12568.

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Kirkpatrick, Keith. "Algorithmic poverty." Communications of the ACM 64, no. 10 (2021): 11–12. http://dx.doi.org/10.1145/3479977.

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Davis, Jenny L., Apryl Williams, and Michael W. Yang. "Algorithmic reparation." Big Data & Society 8, no. 2 (2021): 205395172110448. http://dx.doi.org/10.1177/20539517211044808.

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Machine learning algorithms pervade contemporary society. They are integral to social institutions, inform processes of governance, and animate the mundane technologies of daily life. Consistently, the outcomes of machine learning reflect, reproduce, and amplify structural inequalities. The field of fair machine learning has emerged in response, developing mathematical techniques that increase fairness based on anti-classification, classification parity, and calibration standards. In practice, these computational correctives invariably fall short, operating from an algorithmic idealism that do
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Dissertations / Theses on the topic "Algorithmic"

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Davidsdottir, Agnes. "Algorithms, Turing machines and algorithmic undecidability." Thesis, Uppsala universitet, Algebra och geometri, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-441282.

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Li, Quan Ph D. Massachusetts Institute of Technology. "Algorithms and algorithmic obstacles for probabilistic combinatorial structures." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115765.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 209-214).<br>We study efficient average-case (approximation) algorithms for combinatorial optimization problems, as well as explore the algorithmic obstacles for a variety of discrete optimization problems arising in the theory of random graphs, statistics and machine learning. In particular, we consider the average-case optimization for three NP-hard combinatorial optimization problems: La
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von, Dincklage D. "Algorithmic optimizations." Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3284474.

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Bădoiu, Mihai 1978. "Algorithmic embeddings." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37898.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.<br>Includes bibliographical references (p. 233-242).<br>We present several computationally efficient algorithms, and complexity results on low distortion mappings between metric spaces. An embedding between two metric spaces is a mapping between the two metric spaces and the distortion of the embedding is the factor by which the distances change. We have pioneered theoretical work on relative (or approximation) version of this problem. In this setting, the question is the followi
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Loon, Joyce van. "Algorithmic pricing." Maastricht : Maastricht : Universitaire Pers ; University Library, Universiteit Maastricht [host], 2009. http://arno.unimaas.nl/show.cgi?fid=14955.

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Roio, Denis. "Algorithmic sovereignty." Thesis, University of Plymouth, 2018. http://hdl.handle.net/10026.1/11101.

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This thesis describes a practice based research journey across various projects dealing with the design of algorithms, to highlight the governance implications in design choices made on them. The research provides answers and documents methodologies to address the urgent need for more awareness of decisions made by algorithms about the social and economical context in which we live. Algorithms consitute a foundational basis across different fields of studies: policy making, governance, art and technology. The ability to understand what is inscribed in such algorithms, what are the consequences
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Eriksson, Daniel. "Algorithmic Design of Graphical Resources for Games Using Genetic Algorithms." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139332.

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Producing many varying instances of the same type of graphical resource for games can be of interest, such as trees or foliage. But when randomly generating graphical resources, you can often end up with many similar looking results or perhaps results that doesn't look like what it is meant to look like. This work investigates whether genetic algorithms can be applied to produce greater varying results when generating graphical resources by basing the fitness of each individual for each genetic generation on how similar the graphical resource is to previously generated resources. This work con
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Mehta, Aranyak. "Algorithmic Game Theory." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7220.

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The interaction of theoretical computer science with game theory and economics has resulted in the emergence of two very interesting research directions. First, it has provided a new model for algorithm design, which is to optimize in the presence of strategic behavior. Second, it has prompted us to consider the computational aspects of various solution concepts from game theory, economics and auction design which have traditionally been considered mainly in a non-constructive manner. In this thesis we present progress along both these directions. We first consider optimization problems that a
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Gidney, Mark Sanford. "Algorithmic visual servoing." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ29465.pdf.

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Raczinski, Fania. "Algorithmic meta-creativity." Thesis, De Montfort University, 2016. http://hdl.handle.net/2086/17603.

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Tl;dr: Using computers to produce creative artefacts is a form of computational creativity. Using creative techniques computationally is creative computing. Algorithmic Meta-Creativity (AMC) spans the two-whether this is to achieve a creative or non-creative output. Creativity in humans needs to be interpreted differently to machines. Humans and machines differ in many ways, we have different 'brains/memory', 'thinking processes/software' and 'bodies/hardware'. Often creative output by machines is judged in human terms. Computers which are truly artificially intelligent might be capable of tru
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Books on the topic "Algorithmic"

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Ebers, Martin, and Marta Cantero Gamito, eds. Algorithmic Governance and Governance of Algorithms. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50559-2.

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Hutchinson, Alan. Algorithmic learning. Clarendon Press, 1994.

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Amoore, Louise. Algorithmic Life. Routledge, 2015. http://dx.doi.org/10.4324/9781315723242.

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Portuese, Aurelien, ed. Algorithmic Antitrust. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85859-9.

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Mishra, Bhubaneswar. Algorithmic Algebra. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4344-1.

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Condon, Anne, David Harel, Joost N. Kok, Arto Salomaa, and Erik Winfree, eds. Algorithmic Bioprocesses. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88869-7.

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Hougardy, Stefan, and Jens Vygen. Algorithmic Mathematics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39558-6.

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Kalpokas, Ignas. Algorithmic Governance. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31922-9.

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Nierhaus, Gerhard. Algorithmic Composition. Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-75540-2.

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Hromkovic, Juraj. Algorithmic Adventures. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85986-4.

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Book chapters on the topic "Algorithmic"

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Weik, Martin H. "algorithmic." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_478.

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Leiserson, Charles E. "Algorithmic analysis of multithreaded algorithms." In Algorithms and Computation. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63890-3_15.

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Harel, David, and Yishai Feldman. "Algorithmic Methods." In Algorithmics. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-27266-0_4.

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Gentsch, Peter. "Algorithmic Marketing." In Dialogmarketing Perspektiven 2018/2019. Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-25583-1_3.

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Liu, Andy, George Sicherman, and Takayuki Yoshigahara. "Algorithmic Puzzles." In The Puzzles of Nobuyuki Yoshigahara. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62896-3_4.

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Nešetřil, Jaroslav, and Patrice Ossona de Mendez. "Algorithmic Applications." In Algorithms and Combinatorics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27875-4_18.

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Geiser, Juergen. "Algorithmic Part." In Multicomponent and Multiscale Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15117-5_3.

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Mahlke, Debora. "Algorithmic Implementation." In A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs. Vieweg+Teubner, 2011. http://dx.doi.org/10.1007/978-3-8348-9829-6_7.

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Schröder, Bernd S. W. "Algorithmic Aspects." In Ordered Sets. Birkhäuser Boston, 2003. http://dx.doi.org/10.1007/978-1-4612-0053-6_12.

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Li, Ming, and Paul Vitányi. "Algorithmic Complexity." In An Introduction to Kolmogorov Complexity and Its Applications. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2606-0_2.

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Conference papers on the topic "Algorithmic"

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Burova, Adeliya Yu. "Recurrent Difference Digital Filtering Algorithm Without Algorithmic Multiplication Operations." In 2025 27th International Conference on Digital Signal Processing and its Applications (DSPA). IEEE, 2025. https://doi.org/10.1109/dspa64310.2025.10977906.

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Shi, Zhongyi, Fuzhang Wu, Weibin Zeng, Yan Kong, Sicheng Shen, and Yanjun Wu. "Algorithmic Inversion: A Learnable Algorithm Representation for Code Generation." In 2025 IEEE/ACM 33rd International Conference on Program Comprehension (ICPC). IEEE, 2025. https://doi.org/10.1109/icpc66645.2025.00054.

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Rainey, Craig, and Min Chen. "Algorithmic Stock Trading Strategies." In 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2024. http://dx.doi.org/10.1109/mipr62202.2024.00078.

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Danks, David, and Alex John London. "Algorithmic Bias in Autonomous Systems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/654.

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Algorithms play a key role in the functioning of autonomous systems, and so concerns have periodically been raised about the possibility of algorithmic bias. However, debates in this area have been hampered by different meanings and uses of the term, "bias." It is sometimes used as a purely descriptive term, sometimes as a pejorative term, and such variations can promote confusion and hamper discussions about when and how to respond to algorithmic bias. In this paper, we first provide a taxonomy of different types and sources of algorithmic bias, with a focus on their different impacts on the
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Wilder, Bryan. "Algorithmic Social Intervention." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/840.

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Social and behavioral interventions are a critical tool for governments and communities to tackle deep-rooted societal challenges such as homelessness, disease, and poverty. However, real-world interventions are almost always plagued by limited resources and limited data, which creates a computational challenge: how can we use algorithmic techniques to enhance the targeting and delivery of social and behavioral interventions? The goal of my thesis is to provide a unified study of such questions, collectively considered under the name "algorithmic social intervention". This proposal introduces
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Diberardino, Nathalie, Clair Baleshta, and Luke Stark. "Algorithmic Harms and Algorithmic Wrongs." In FAccT '24: The 2024 ACM Conference on Fairness, Accountability, and Transparency. ACM, 2024. http://dx.doi.org/10.1145/3630106.3659001.

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A. N., Rybalov. "GENERIC COMPLEXITY OF ALGORITHMIC PROBLEMS." In Mechanical Science and Technology Update. Omsk State Technical University, 2022. http://dx.doi.org/10.25206/978-5-8149-3453-6-2022-10-14.

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Generic approach is one of the approaches to the study of algorithmic problems for almost all inputs, born at the intersection of computational algebra and computer science. Within the framework of this approach, algorithms are studied that solve a problem for almost all inputs, and for the remaining rare inputs give an undefined answer. This review reflects two areas of research of generic complexity of algorithmic problems in algebra, mathematical logic, number theory, and theoretical computer science. The first direction is devoted to the construction of generic algorithms for problems that
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Garnham, Ignacio, and Rachel Smith. "The Social Life of Algorithmic Values: Examining the Impact of Value-Based Frameworks in Everyday Life." In 14th Scandinavian Conference on Artificial Intelligence SCAI 2024, June 10-11, 2024, Jönköping, Sweden. Linköping University Electronic Press, 2024. http://dx.doi.org/10.3384/ecp208012.

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Value-based frameworks are widely used to guide the design of algorithms, yet their influence in mediating users’ perception and use of algorithm-driven technologies is vastly understudied. Moreover, there is a need to move research beyond a focus on human-algorithm interaction to account for how the values these frameworks promote – algorithmic values – become socialised outside the boundaries of the (human-algorithm) interaction and how they influence everyday practices that are not algorithmically mediated. This paper traces the entanglement of algorithmic values and everyday life by mappin
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PAVLENCO, Mihaela. "The development of algorithmical skills at children from older preschool age." In Ştiință și educație: noi abordări și perspective. "Ion Creanga" State Pedagogical University, 2023. http://dx.doi.org/10.46727/c.v2.24-25-03-2023.p211-217.

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Algorithms and the process of forming the algorithmic skills at preschoolers are an effective means of developing the premises necessary for learning activities, because an algorithm is a way for accept and maintain the purpose of the future activity, it is a sequence of operations necessary for solving practical and educational problems. Mastering the algorithm gives the child the possibility to transfer the method of solving a certain problem in similar contexts. Actions of control, self-control and correction are also characteristic the algorithmic activities of humans. So, the algorithms i
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Czakoova, Krisztina. "DEVELOPING ALGORITHMIC THINKING BY EDUCATIONAL COMPUTER GAMES." In eLSE 2020. University Publishing House, 2020. http://dx.doi.org/10.12753/2066-026x-20-003.

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Basics of algorithmic thinking should not be limited to create right solutions and express them by a computer program, but should also be used a suitable methodology based on problem solving, preferably in a playful way. In many cases at school most of the learners consider the topic of algorithms as hard and not very attractive. For beginners in programming the knowledge of specific algorithms is not so important. The ability to understand principles of algorithms, as well as to find own algorithms for new problems are more desirable. One main educational objective is to know that an algorith
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Reports on the topic "Algorithmic"

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Marty, Frédéric, and Thierry Warin. Deciphering Algorithmic Collusion: Insights from Bandit Algorithms and Implications for Antitrust Enforcement. CIRANO, 2023. http://dx.doi.org/10.54932/iwpg7510.

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This paper examines algorithmic collusion from legal and economic perspectives, highlighting the growing role of algorithms in digital markets and their potential for anti-competitive behavior. Using bandit algorithms as a model, traditionally applied in uncertain decision-making contexts, we illuminate the dynamics of implicit collusion without overt communication. Legally, the challenge is discerning and classifying these algorithmic signals, especially as unilateral communications. Economically, distinguishing between rational pricing and collusive patterns becomes intricate with algorithm-
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Turnhout, Esther, Alexander Supper, and Andreas Weber. Algorithmic Summer School 2023. Netherlands Graduate Research School of Science, Technology and Modern Culture, 2023. http://dx.doi.org/10.3990/1.2666-2892.2023.02.

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Bullo, Francesco. Algorithmic Coordination in Robotic Networks. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada535241.

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Morton, D. P. Algorithmic advances in stochastic programming. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10186619.

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Frigo, Matthew. Algorithmic Advances for Software Radios. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada419766.

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Brown, Christopher W. Algorithmic Reformulation of Polynomial Problems. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada469251.

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Angelova, Victoria, Will Dobbie, and Crystal Yang. Algorithmic Recommendations and Human Discretion. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31747.

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Liu, Zhuang, Michael Sockin, and Wei Xiong. Data Privacy and Algorithmic Inequality. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31250.

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Milanez, Anna, Annikka Lemmens, and Carla Ruggiu. Algorithmic management in the workplace. Organisation for Economic Co-Operation and Development (OECD), 2025. https://doi.org/10.1787/287c13c4-en.

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Moses Charikar. Algorithmic Techniques for Massive Data Sets. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/881082.

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