Letteratura scientifica selezionata sul tema "Evolution Grammaticale"
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Articoli di riviste sul tema "Evolution Grammaticale":
Botne, Robert. "The Evolution of Future Tenses from Serial 'Say' Constructions in Central Eastern Bantu". Diachronica 15, n. 2 (1 gennaio 1998): 207–30. http://dx.doi.org/10.1075/dia.15.2.02bot.
O'Neill, M., e C. Ryan. "Grammatical evolution". IEEE Transactions on Evolutionary Computation 5, n. 4 (2001): 349–58. http://dx.doi.org/10.1109/4235.942529.
Nicolau, Miguel. "Understanding grammatical evolution: initialisation". Genetic Programming and Evolvable Machines 18, n. 4 (25 luglio 2017): 467–507. http://dx.doi.org/10.1007/s10710-017-9309-9.
Bartoli, Alberto, Mauro Castelli e Eric Medvet. "Weighted Hierarchical Grammatical Evolution". IEEE Transactions on Cybernetics 50, n. 2 (febbraio 2020): 476–88. http://dx.doi.org/10.1109/tcyb.2018.2876563.
Ortega, Alfonso, Marina de la Cruz e Manuel Alfonseca. "Christiansen Grammar Evolution: Grammatical Evolution With Semantics". IEEE Transactions on Evolutionary Computation 11, n. 1 (febbraio 2007): 77–90. http://dx.doi.org/10.1109/tevc.2006.880327.
Dempsey, Ian, Michael O'Neill e Anthony Brabazon. "Constant creation in grammatical evolution". International Journal of Innovative Computing and Applications 1, n. 1 (2007): 23. http://dx.doi.org/10.1504/ijica.2007.013399.
He, Pei, Colin G. Johnson e HouFeng Wang. "Modeling grammatical evolution by automaton". Science China Information Sciences 54, n. 12 (dicembre 2011): 2544–53. http://dx.doi.org/10.1007/s11432-011-4411-8.
Hugosson, Jonatan, Erik Hemberg, Anthony Brabazon e Michael O’Neill. "Genotype representations in grammatical evolution". Applied Soft Computing 10, n. 1 (gennaio 2010): 36–43. http://dx.doi.org/10.1016/j.asoc.2009.05.003.
Cathcart, Chundra, Gerd Carling, Filip Larsson, Niklas Johansson e Erich Round. "Areal pressure in grammatical evolution". Diachronica 35, n. 1 (16 aprile 2018): 1–34. http://dx.doi.org/10.1075/dia.16035.cat.
YAMAMOTO, Risako, Qingshuang YE, Hideyuki SUGIURA, Yi ZUO e Eisuke KITA. "Improvement of Grammatical Differential Evolution". Proceedings of The Computational Mechanics Conference 2016.29 (2016): 007. http://dx.doi.org/10.1299/jsmecmd.2016.29.007.
Tesi sul tema "Evolution Grammaticale":
Harper, Robin Thomas Ross Computer Science & Engineering Faculty of Engineering UNSW. "Enhancing grammatical evolution". Awarded by:University of New South Wales. Computer Science & Engineering, 2010. http://handle.unsw.edu.au/1959.4/44843.
Georgiou, Loukas. "Constituent grammatical evolution". Thesis, Bangor University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.569460.
Zhang, Andrew H. M. Eng Massachusetts Institute of Technology. "Structured Grammatical Evolution applied to program synthesis". Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122995.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 27).
Grammatical Evolution (GE) is an evolutionary algorithm that is gaining popularity due to its ability to solve problems where it would be impossible to explore every solution within a realistic time. Structured Grammatical Evolution (SGE) was developed to overcome some of the shortcomings of GE, such as locality issues as well as wrapping around the genotype to complete the phenotype. In this paper, we apply SGE to program synthesis, where the computer must generate code to solve algorithmic problems. SGE was improved upon, because the current definition of SGE does not work. Given that the solution space is very large for possible codes, we aim to improve the efficiency of GE in converging to the correct solution. We present a method in which to remove cycles from a grammar for SGE, to be able to make sure that a genotype matches to a phenotype with reusing parts of the genotype, and analyze results to shed insight on future improvements.
by Andrew H. Zhang.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Crochepierre, Laure. "Apprentissage automatique interactif pour les opérateurs du réseau électrique". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0112.
In the energy transition context and the increase in interconnections between the electricity transmission networks in Europe, the French network operators must now deal with more fluctuations and new network dynamics. To guarantee the safety of the network, operators rely on computer software that allows them to carry out simulations or to monitor the evolution of indicators created manually by experts, thanks to their knowledge of the operation of the network. The French electricity transmission network operator RTE (Réseau de Transport d'Electricité) is particularly interested in developing tools to assist operators in monitoring flows on power lines. Flows are notably important to maintain the network in a safe state, guaranteeing the safety of equipment and people. However, the indicators used are not easy to update because of the expertise required to construct and analyze them.In order to address the stated problem, this thesis aims at constructing indicators, in the form of symbolic expressions, to estimate flows on power lines. The problem is studied from the Symbolic Regression perspective and investigated using both Grammatical Evolution and Reinforcement Learning approaches in which explicit and implicit expert knowledge is taken into account. Explicit knowledge about the physics and expertise of the electrical domain is represented in the form of a Context-Free Grammar to limit the functional space from which an expression is created. A first approach of Interactive Grammatical Evolution proposes to incrementally improve found expressions by updating a grammar between evolutionary learnings. Expressions are obtained on real-world data from the network history, validated by an analysis of learning metrics and an interpretability evaluation. Secondly, we propose a reinforcement approach to search in a space delimited by a Context-Free Grammar in order to build a relevant symbolic expression to applications involving physical constraints. This method is validated on state-of-the-art Symbolic Regression benchmarks and also on a dataset with physical constraints to assess its interpretability.Furthermore, in order to take advantage of the complementarities between the capacities of machine learning algorithms and the expertise of network operators, interactive Symbolic Regression algorithms are proposed and integrated into interactive platforms. Interactivity allows updating the knowledge represented in grammatical form and analyzing, interacting with, and commenting on the solutions found by the different approaches. These algorithms and interactive interfaces also aim to take into account implicit knowledge, which is more difficult to formalize, through interaction mechanisms based on suggestions and user preferences
Deodhar, Sushamna Shriniwas. "Using Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions in Genetic Epidemiology". NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-10302009-181439/.
Neupane, Aadesh. "Emergence of Collective Behaviors in Hub-Based Colonies using Grammatical Evolution and Behavior Trees". BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8827.
Eilert, Pernilla. "Learning behaviour trees for simulated fighter pilots in airborne reconnaissance missions : A grammatical evolution approach". Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-156165.
De, Silva Anthony Mihirana. "Grammar based feature generation for time-series prediction". Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10278.
Mehrmand, Arash. "A Factorial Experiment on Scalability of Search-based Software Testing". Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4224.
Noorian, Farzad. "Risk Management using Model Predictive Control". Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14282.
Libri sul tema "Evolution Grammaticale":
O’Neill, Michael, e Conor Ryan. Grammatical Evolution. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4.
Ryan, Conor, Michael O'Neill e JJ Collins, a cura di. Handbook of Grammatical Evolution. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78717-6.
Dempsey, Ian, Michael O’Neill e Anthony Brabazon. Foundations in Grammatical Evolution for Dynamic Environments. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00314-1.
O'Neill, Michael. Grammatical evolution: Evolutionary automatic programming in an arbitrary language. Boston, MA: Kluwer Academic Publishers, 2004.
O'Neill, Michael. Grammatical evolution: Evolutionary automatic programming in an arbitrary language. Boston: Kluwer Academic Publishers, 2003.
O'Neill, Michael. Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Boston, MA: Springer US, 2003.
Brancato, Francesco. Creazione ed evoluzione: La grammatica di un dialogo possibile. Troino (Enna): Città aperta, 2009.
O'Neill, Michael, Conor Ryan e JJ Collins. Handbook of Grammatical Evolution. Springer, 2018.
Handbook of Grammatical Evolution. Springer, 2019.
O'Neill, Michael, Ian Dempsey e Anthony Brabazon. Foundations in Grammatical Evolution for Dynamic Environments. Springer, 2010.
Capitoli di libri sul tema "Evolution Grammaticale":
O’Neil, Michael, e Conor Ryan. "Grammatical Evolution". In Grammatical Evolution, 33–47. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_4.
O’Neil, Michael, e Conor Ryan. "Introduction". In Grammatical Evolution, 1–4. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_1.
O’Neil, Michael, e Conor Ryan. "Survey Of Evolutionary Automatic Programming". In Grammatical Evolution, 5–21. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_2.
O’Neil, Michael, e Conor Ryan. "Lessons From Molecular Biology". In Grammatical Evolution, 23–32. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_3.
O’Neil, Michael, e Conor Ryan. "Four Examples of Grammatical Evolution". In Grammatical Evolution, 49–62. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_5.
O’Neil, Michael, e Conor Ryan. "Analysis of Grammatical Evolution". In Grammatical Evolution, 63–77. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_6.
O’Neil, Michael, e Conor Ryan. "Crossover in Grammatical Evolution". In Grammatical Evolution, 79–98. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_7.
O’Neil, Michael, e Conor Ryan. "Extensions & Applications". In Grammatical Evolution, 99–128. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_8.
O’Neil, Michael, e Conor Ryan. "Conclusions & Future Work". In Grammatical Evolution, 129–32. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0447-4_9.
De Silva, Anthony Mihirana, e Philip H. W. Leong. "Grammatical Evolution". In SpringerBriefs in Applied Sciences and Technology, 25–33. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-287-411-5_3.
Atti di convegni sul tema "Evolution Grammaticale":
Ryan, Conor. "Grammatical evolution". In the 11th annual conference companion. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1570256.1570408.
Ryan, Conor M. "Grammatical evolution". In the 2007 GECCO conference companion. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1274000.1274126.
Timperley, Christopher, e Susan Stepney. "Reflective Grammatical Evolution". In Artificial Life 14: International Conference on the Synthesis and Simulation of Living Systems. The MIT Press, 2014. http://dx.doi.org/10.7551/978-0-262-32621-6-ch013.
Medvet, Eric. "Hierarchical grammatical evolution". In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3067695.3075972.
Timperley, Christopher, e Susan Stepney. "Reflective Grammatical Evolution". In Artificial Life 14: International Conference on the Synthesis and Simulation of Living Systems. The MIT Press, 2014. http://dx.doi.org/10.1162/978-0-262-32621-6-ch013.
Ryan, Conor. "Grammatical evolution tutorial". In the 12th annual conference comp. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1830761.1830900.
Dempsey, Ian, Michael O'Neill e Anthony Brabazon. "Meta-grammar constant creation with grammatical evolution by grammatical evolution". In the 2005 conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1068009.1068289.
Murphy, Eoin, Michael O'Neill, Edgar Galvan-Lopez e Anthony Brabazon. "Tree-adjunct grammatical evolution". In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586497.
OGURA, MIEKO, e WILLIAM S.-Y. WANG. "EVOLUTION OF GRAMMATICAL FORMS". In Proceedings of the 8th International Conference (EVOLANG8). WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814295222_0032.
Medvet, Eric, Fabio Daolio e Danny Tagliapietra. "Evolvability in grammatical evolution". In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3071178.3071298.