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With the advent of modernism, trends in art have shifted toward a greater autonomy in the definition, and practice of art. Art is no longer bounded by the constraints of traditional conceptions of beauty, and more importantly, of its primary function of representation. The result of such trends is, unfortunately, the widening distance between the culture of the art connoisseurs, and that of the larger public. Especially in today's highly modernized, and capitalist society, where fast gratification is widely available with the advanced technologies, art is often perceived as something esoteric, or something irrelevant to one's daily life. At this confusing time in the history of art, there seems to be no right answer to how art or the experience of art should be defined.

One may suggest that aesthetic experience in response to works of art should be defined as an experience qualitatively different from everyday experience. It is apparent that works of art can allow people the feelings of admiration, fascination, and awe, which are certainly distinguishable from everyday emotions; however, the value of art would truly manifest only when it is enjoyed as a part of our daily lives. Among its countless functions, one of the irremovable functions of art is to be consumed, and to be enjoyed, as if it is nearly impossible to ponder the meaning of art without considering the presence of its audience or appreciator.

But still there remain some big questions, such as about what to appreciate, or what to qualify as a work of art. Despite the social notion on the judgment of taste, which has been reinforced by the gap between the two cultures, of the art experts and of the public at large, there is no innate hierarchical measure in judgments of taste, or of art itself. The efforts, however, have been made in determining the value of works of art, either for matters of convenience or sometimes for one's benefit. With the rise of the art market, the works of art are typically being evaluated according to the two separate terms: an aesthetic, and a commercial value. Although setting the price for artwork, the product of human gift, might be considered as an attempt to degrade human creativity, the commercial value is now an inseparable part of the artwork as a whole, indirectly representing people's demand in art.

Nowadays, the works of art that are preferred by the larger public appear to be the works that can offer unquestionable beauty without invoking any complex philosophical questions. Such artworks are produced with clear objectives to fulfill human desire for beauty, functioning as an instrument to offer visual satisfaction. Among those works, some observable similarities can be found as listed below.

- There are (preferably) no discernible figures or shapes;

- The mood or atmosphere of an artwork provides positive (or at least neural) connotations;

- Any negative reactions (e.g. fear, contempt, disgust, and etc.) should not be evoked to the viewers

If what has been presented exceeds the underlying aesthetic or philosophical intention in terms of significance, the mere appearance of an artwork then becomes the primary reason for its existence. In the production of such kind of works, the presence of the creators or artists loses its importance. And the potential of artificial intelligence as an art-maker begins to reveal at this very point.

THE PROJECT

The project had been proceeded with the aims to shed light on the true value of art, and to challenge the traditional conceptions of art. The code used in the project are heavily borrowed from ArtGAN (https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN). ArtGAN proposes a novel framework to synthetically generate more challenging and complex images, which is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The model suggests innovative approaches for conditional image synthesis, allowing backpropagation of the loss function with respect to the labels to the generator from the discriminator. As a result, ArtGAN exhibits the phase of training that is dramatically less susceptible to mode collapse compared to other traditional models.

The major change to ArtGAN is the use of customized data loader function to facilitate a more of general use. The new label Abstract Art has been added to the original Wikiart dataset. Abstract Art contains 4,000 images (1,000 collected from web sources, 3,000 data augmented) that qualify the above-listed characteristics.

Sample of the real artwork

Sample of the generated artwork

Although it should be acknowledged that there still are numerous limitations of an intelligent agent in the creative field of art, the results have shown that the images generated by artificial agents can elegantly fulfill one of the pivotal functions of art, offering an unconditional visual satisfaction to the viewers. The generative model is also capable of generating a massive number of images. Thus, despite the absence of the traditional artists, the images generated by ArtGAN, and by other generative models, have revealed their future potentials to satisfy the larger demographics of people in terms of appearance and a method of production.

With the advent of modernism, trends in art have shifted toward a greater autonomy in the definition, and practice of art. Art is no longer bounded by the constraints of traditional conceptions of beauty, and more importantly, of its primary function of representation. The result of such trends is, unfortunately, the widening distance between the culture of the art connoisseurs, and that of the larger public. Especially in today's highly modernized, and capitalist society, where fast gratification is widely available with the advanced technologies, art is often perceived as something esoteric, or something irrelevant to one's daily life. At this confusing time in the history of art, there seems to be no right answer to how art or the experience of art should be defined.

One may suggest that aesthetic experience in response to works of art should be defined as an experience qualitatively different from everyday experience. It is apparent that works of art can allow people the feelings of admiration, fascination, and awe, which are certainly distinguishable from everyday emotions; however, the value of art would truly manifest only when it is enjoyed as a part of our daily lives. Among its countless functions, one of the irremovable functions of art is to be consumed, and to be enjoyed, as if it is nearly impossible to ponder the meaning of art without considering the presence of its audience or appreciator.

But still there remain some big questions, such as about what to appreciate, or what to qualify as a work of art. Despite the social notion on the judgment of taste, which has been reinforced by the gap between the two cultures, of the art experts and of the public at large, there is no innate hierarchical measure in judgments of taste, or of art itself. The efforts, however, have been made in determining the value of works of art, either for matters of convenience or sometimes for one's benefit. With the rise of the art market, the works of art are typically being evaluated according to the two separate terms: an aesthetic, and a commercial value. Although setting the price for artwork, the product of human gift, might be considered as an attempt to degrade human creativity, the commercial value is now an inseparable part of the artwork as a whole, indirectly representing people's demand in art.

Nowadays, the works of art that are preferred by the larger public appear to be the works that can offer unquestionable beauty without invoking any complex philosophical questions. Such artworks are produced with clear objectives to fulfill human desire for beauty, functioning as an instrument to offer visual satisfaction. Among those works, some observable similarities can be found as listed below.

- There are (preferably) no discernible figures or shapes;

- The mood or atmosphere of an artwork provides positive (or at least neural) connotations;

- Any negative reactions (e.g. fear, contempt, disgust, and etc.) should not be evoked to the viewers

If what has been presented exceeds the underlying aesthetic or philosophical intention in terms of significance, the mere appearance of an artwork then becomes the primary reason for its existence. In the production of such kind of works, the presence of the creators or artists loses its importance. And the potential of artificial intelligence as an art-maker begins to reveal at this very point.

THE PROJECT

The project had been proceeded with the aims to shed light on the true value of art, and to challenge the traditional conceptions of art. The code used in the project are heavily borrowed from ArtGAN (https://github.com/cs-chan/ArtGAN/tree/master/ArtGAN). ArtGAN proposes a novel framework to synthetically generate more challenging and complex images, which is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The model suggests innovative approaches for conditional image synthesis, allowing backpropagation of the loss function with respect to the labels to the generator from the discriminator. As a result, ArtGAN exhibits the phase of training that is dramatically less susceptible to mode collapse compared to other traditional models.

The major change to ArtGAN is the use of customized data loader function to facilitate a more of general use. The new label Abstract Art has been added to the original Wikiart dataset. Abstract Art contains 4,000 images (1,000 collected from web sources, 3,000 data augmented) that qualify the above-listed characteristics.

Sample of the real artwork

Sample of the generated artwork

Although it should be acknowledged that there still are numerous limitations of an intelligent agent in the creative field of art, the results have shown that the images generated by artificial agents can elegantly fulfill one of the pivotal functions of art, offering an unconditional visual satisfaction to the viewers. The generative model is also capable of generating a massive number of images. Thus, despite the absence of the traditional artists, the images generated by ArtGAN, and by other generative models, have revealed their future potentials to satisfy the larger demographics of people in terms of appearance and a method of production.

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KJ Ha
- 2 min read

Nature of Code: Genetic Algorithm Design Exercise

Scenario

When I heard the concept of genetic algorithm for the first time, I automatically thought it is perfect for games, like in the smart rocket example. To keep it simple and sweet, I propose the Tetris game scenario.

I first wondered whether the population in this scenario should be the shape of blocks or their movements. But soon I figured, it makes more sense to set the population to be the movements of each block when considering the objective of the game.

Phenotype and Genotype

Different types of tetrominoes

In short, the main factor that needs to be evolving is the movement pattern of each block type. For example, while rotating the O-block is just a waste of time, rotating J-block can give us different results each time. However, to achieve the optimal result, many other factors need to be taken into consideration.

Pictures showing very different phases of the game.

Here are some factors that affect the final result of the game.

1. The total height of each vertical line (ex: 4+4+4+4+5+6+4+4+4+2=41) => need to be minimized

2. The total number of cleared lines. => need to be maximized

3. The total number of holes (ex: 3) => need to be minimized

4. The total number of blocks above the holes (ex: 4) => need to be minimized

5. The standard deviation of heights (ex: 0.94339811320566)

6. The number of faces of a descending block that will touch the ground. (ex: 2)

7. The number of faces of a descending block that will touch the wall. (ex: 2)

Fitness Function

The objective of the Tetris game is to get the highest score by completing as many horizontal lines of blocks within the longest survival time.

Mutation and Crossover

Run the game multiple times with random values for seven factors that affect the final result. (Now, I only can think of seven, but there could be more factors.)
Take high-scoring values of the factors.
Mix high-scoring values across different games until achieving the highest score.

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