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dc.contributor.authorSalem, Mohammed
dc.contributor.authorMora, Antonio M (1)
dc.contributor.authorMerelo, Juan Julián
dc.contributor.authorGarcía-Sánchez, Pablo
dc.date2018
dc.date.accessioned2020-09-02T10:33:25Z
dc.date.available2020-09-02T10:33:25Z
dc.identifier.citationSalem M., Mora A.M., Merelo J.J., García-Sánchez P. (2018) Evolving a TORCS Modular Fuzzy Driver Using Genetic Algorithms. In: Sim K., Kaufmann P. (eds) Applications of Evolutionary Computation. EvoApplications 2018. Lecture Notes in Computer Science, vol 10784. Springer, Cham. https://doi.org/10.1007/978-3-319-77538-8_24es_ES
dc.identifier.isbn9783319775371
dc.identifier.issn0302-9743
dc.identifier.urihttps://reunir.unir.net/handle/123456789/10477
dc.descriptionPonencia de la conferencia "21st International Conference on Applications of Evolutionary Computation, EvoApplications 2018; parma; Italy; 4 April 2018 through 6 April 2018"es_ES
dc.description.abstractThis work presents an evolutionary approach to optimize the parameters of a Fuzzy-based autonomous driver for the open simulated car racing game (TORCS). Using evolutionary algorithms, we intend to optimize a modular fuzzy agent designed to determine the optimal target speed as well as the steering angle during the race. The challenge in this kind of fuzzy systems is the design of the membership functions, which is usually done through a trial and error process, but in this paper an adapted real-coded Genetic Algorithm with two different fitness functions - has been applied to find the best values for these parameters, obtaining a robust design for the TORCS controller. The evolved drivers were tested and evaluated competing against other TORCS controllers in practice mode, without rivals, and real races. The optimized fuzzy-controllers yield a very good performance, mainly in tracks that have many turning points, which are, in turn, the most difficult for any autonomous agent. Thus, this is a real enhancement of the baseline fuzzy controllers which had several difficulties to drive in this kind of circuits.es_ES
dc.language.isoenges_ES
dc.publisherLecture Notes in Computer Sciencees_ES
dc.relation.ispartofseries;vol. 10784
dc.relation.urihttps://link.springer.com/chapter/10.1007%2F978-3-319-77538-8_24es_ES
dc.rightsrestrictedAccesses_ES
dc.subjectvideogameses_ES
dc.subjectfuzzy controlleres_ES
dc.subjectTORCSes_ES
dc.subjectsteering controles_ES
dc.subjectoptimizationes_ES
dc.subjectgenetic algorithmses_ES
dc.subjectScopus(2)es_ES
dc.titleEvolving a TORCS Modular Fuzzy Driver Using Genetic Algorithmses_ES
dc.typebookPartes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttps://doi.org/10.1007/978-3-319-77538-8_24


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