2018
DOI: 10.1080/17445760.2017.1422185
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Improving cellular automata scheduling through dynamics control

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Cited by 6 publications
(3 citation statements)
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“…In Collados-Lara et al (2019), authors propose CA to simulate potential future impacts of climate change on snow covered areas, whereas in Gounaridis et al (2019) an approach to explore future land use/cover change under different socio-economic realities and scales is presented. Scheduling is another field where CA has been profusely in use (Carvalho and Carneiro 2019). Another recent CA approach for classification is Uzun et al (2018).…”
Section: Cellular Automata For Pattern Recognitionmentioning
confidence: 99%
“…In Collados-Lara et al (2019), authors propose CA to simulate potential future impacts of climate change on snow covered areas, whereas in Gounaridis et al (2019) an approach to explore future land use/cover change under different socio-economic realities and scales is presented. Scheduling is another field where CA has been profusely in use (Carvalho and Carneiro 2019). Another recent CA approach for classification is Uzun et al (2018).…”
Section: Cellular Automata For Pattern Recognitionmentioning
confidence: 99%
“…CA are totally discrete mathematical models based on the livelihood of cellular organisms, a naturally occurring process which dictates the survival of such cells based on their behavior (implemented as CA rules) while interacting with the environment conditions they are exposed to (the cell neighborhood) [Rozenberg et al (2012)]. CA are widely used in the literature [Sarkar (2000)] and, among the most known applications, the following can be mentioned: (i) modeling of biological and physical systems [Vichniac (1984); Ermentrout and Edelstein-Keshet (1993); Maerivoet and De Moor (2005); Alizadeh (2011); Ghimire et al (2013); Feliciani and Nishinari (2016); Mattei et al (2018)]; (ii) investigation of new computational paradigms [Hillis (1984); Lent et al (1993); Morita (2008); Yilmaz (2015)]; (iii) proposition of tools for solving various computational problems, such as task scheduling [Swiecicka et al (2006); Carneiro and Oliveira (2013); Carvalho et al (2019)], image processing [Rosin (2010)], computational tasks [Mitchell et al (2005); Oliveira et al (2009)], robotics [Ioannidis et al (2011); Lima and Oliveira (2017)] and, more significantly related to this article, cryptographic models [Wolfram (1986); Gutowitz (1995); Sen et al (2002)].…”
Section: Introductionmentioning
confidence: 99%
“…Existe uma interdisciplinaridade bastante abrangente quando se trata da aplicabilidade do ACs. Podemos citar como exemplo de aplicações: (i) a simulação de sistemas para o entendimento da lógica molecular (LANGTON, 1986), a previsão de mutações genéticas (MIZAS et al, 2008) e a simulação da dinâmica do DNA (MIZAS et al, 2016); (ii) o processo de formação de cristais de gelo, onde cada molécula se agrupa de acordo com formação das moléculas vizinhas (REITER, 2005); (iii) sistemas para simulação de terremotos (OLAMI et al, 1992;GEORGOUDAS et al, 2007) e evacuação emergencial de estruturas comprometidas por algum desastre (LI et al, 2015); (iv) aplicação de ACs no escalonamento de programas para sistemas multiprocessados (CARNEIRO; OLI-VEIRA, 2013;CARVALHO et al, 2018). Na robótica, a aplicação dos ACs foi proposta principalmente para a tarefa de planejamento de rotas para robôs autônomos (TZIONAS et al, 1997;BEHRING et al, 2001;LUCAS, 2006;MARCHESE;NE-GRO, 2006;KOSTAVELIS et al, 2012;ROSENBERG, 2012;IOANNIDIS et al, 2011;IOANNIDIS et al, 2013;FERREIRA et al, 2014;MARTINS et al, 2018), controladores robóticos (LAL et al, 2006;KIM;CHO, 2006), robôs auto-reconfiguráveis (STOY, 2006) e na tarefa de forrageamento (LIMA; OLIVEIRA, 2016; LIMA; OLIVEIRA, 2017).…”
Section: Autômatos Celularesunclassified