Random aesthetic generator

• [PDF File]Chapter 9 Random Numbers - MathWorks

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  Random Numbers This chapter describes algorithms for the generation of pseudorandom numbers with both uniform and normal distributions. 9.1 Pseudorandom Numbers Here is an interesting number: 0.814723686393179 This is the first number produced by the Matlab random number generator with its default settings.

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• [PDF File]Procedural Content Generation via Machine Learning (PCGML)

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  aesthetic in itself. Academic PCG research addresses these challenges, but also explores how PCG can enable new types of game experiences, including games that can adapt to the player. Researchers also address challenges in computational creativity and ways of increasing our understanding of game design through building formal models [1].

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• Abstract arXiv:1801.08624v1 [cs.CV] 25 Jan 2018

  between the generator’s output and true data. Formally, the game between the generator Gand the discriminator Dhas the minimax objective: min G max D E x˘P r [logD(x)]+E z˘P g [log(1 D(G(z))]; (1) where x˘P r are samples from the input data and z˘P g are the random noise samples, G(z) are the generated im-ages using the neural network ...

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• [PDF File]A note on random number generation - The Comprehensive R ...

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  number generation. By “random numbers”, we mean random variates of the uniform U(0,1) distri-bution. More complex distributions can be generated with uniform variates and rejection or inversion methods. Pseudo random number generation aims to seem random whereas quasi random number generation aims to be deterministic but well equidistributed.

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• [PDF File]Interactive Design of Random Aesthetic Abstract Textures by ...

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  random combinations of shapes, composition and render-ing rules. We presented the mathematical description of a texture generator based on an organization in successive layers [10]. As we argue below, the tree organization that we propose in this article is far more general. We show a number of collections of textures made with the AAT ...

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• [PDF File]I 28

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  dom number generator that produced truly random digits from noise.5 2.2 Strachey's Next Step Once there were stored program digital computers, all that remained (for our field to take its first step) was for someone to make literary use of one. I be­ lieve that-in 1952, working on the Manchester Mark I-Christopher Strachey was the first to do so.

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• The Layout Generation Algorithm of Graphic Design Based on ...

  overall layout tidier and more in line with the aesthetic habits of the public. Traditional tasks such as image or voice generation do not consider the introduction of design rules for display. Fig. 1.1. The generated layout of PowerPoint slides through our model Most of the existing graphic design layout works [3-5] use

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