Work

MoMar-LookingOutwards02

Slaves to Armok: God of Blood
Chapter II: Dwarf Fortress

Dwarf Fortress is a procedurally generated game made by brothers Tarn and Zach Adams released in 2006. Development is supported by crowdsourced donations. To play, the player needs to generate a new world through parameters ranging from resources to the length of the world's history. I imagine that the algorithm used to generate the world runs during the duration of the game. It likely randomly generates an elevation then picks areas to have biomes, then randomly picks what lives there and so on.

Graphics are simple text symbols, but they can be replaced with custom tilesets.

I admire the potential immersion that a player, they can literally do anything! The brothers' love for generating random worlds is visible.

The effective complexity of this piece is closer to disorder because the game world is constantly changing due to random events

The video that introduced me to Dwarf Fortress (view at your own discretion NSFW):

https://www.youtube.com/watch?v=0FW23bamIZI

 

Download Link
http://www.bay12forums.com/smf/index.php?topic=126076

Tutorial

https://df-walkthrough.readthedocs.io/en/latest/chapters/chap01-setup-starting.html

gray-LookingOutwards2

AARON

AARON is an AI developed by Harold Cohen to create original paintings. Cohen has been developing the same algorithm since 1973. There's a lot of things I find fascinating about this project. The algorithm is really an evolving thing, with a lot of complex parts. It's a little difficult to find information, but it seems that AARON has some simple imperative rules as well as some learning functions. It's amazing how much the algorithm has changed since its inception. At first, it just did line drawings, then color, then more and more abstract shapes. Its most recent works look like a different artist than the early works:

Painting by AARON from 1995
Image result for AARON harold cohen paintings
04052, a painting done in 2004

 

 

 

 

 

AARON's paintings, I think, are actually more simple than many generative algorithms, and that's something that I find impressive. They are concise.

Harold Cohen has some articles he's written about AARON on his website: http://www.aaronshome.com/aaron/index.html

Here's a video of one of AARON's older paintings: https://www.youtube.com/watch?v=3PA-XApZkso

gray-Interruptions

Observations:

  1. The composition is square.
  2. The composition consists of black lines on a white background
  3. All the lines are the same length.
  4. The lines have randomized slopes, but tend towards vertical.
  5. There are margins that are about the length of two lines.
  6. The height of the rows and width of the columns is half the length of the lines.
  7. There are gaps where multiple lines are missing from a section of the grid, but the number of lines and the shape and position of the gap is fairly random.
  8. About 5-10% of the grid consists of gaps.
  9. There exist lines on the grid within gaps such that they are not adjacent to any other lines.
  10. There are 56 rows and 56 columns.

So I first did the grid of randomized lines that tend to be vertical, and then I wanted to do a weird recursive function to generate the voids as an array of points by starting with one point and then including adjacent points based on a probability. But that was really complicated, so then I saw someone talking about using just a random radius and making points in that radius voids, and I tried that. I added a weighted probability that those points wouldn't actually be voids, based on how far from the center of the circle void they were. That made the edges of my circles more fuzzy. I added a couple other things to add fuzziness. It's still definitely not the same program as Molnar's. Hers is very complex from what I can see. It's really impressive that she did that; it definitely seems like some kind of noise function, and mine is pretty far from that. When I squint I still just see a bunch of circles in mine.

link: https://editor.p5js.org/gray/sketches/LFzBlbk2c

lsh-LookingOutwards02

Inigo Quilez's Happy Jumping (2019) is an incredible project for a few reasons. The project itself is a raymarched shader of a cute character jumping around on a bouncy floor in a surreal landscape. One can easily talk about the impressive technical skill behind this piece. The jumping is believable, the floor bounce is wonderful. What I find admirable about this piece is how whimsical the work is, given the context of the piece. ShaderToy is a host to many technically skilled individuals, a few of which have masters and PhDs in math or physics. This piece breaks a mold of the usual geometric study and invites silliness to an otherwise mathematically focused group. The algorithm behind this piece are available for all to see, but the main backbone is the raymarching algorithm, and movement is done with noise. Inigo has proven that he can easily do photorealism, but lately his sensibility from has time at Pixar has been prevalent in his work. Though infinitely generated, the piece will always be the happy creature jumping along.

View the project in realtime!

ilovit-Reading02

A

Novels are effectively complex. The elements of a novel are ordered by various structures of language, but still various. Letters are arranged into words, but the particular words vary widely. Similarly, words are arranged into sentences and sentences into paragraphs, chapters. To someone who doesn't understand the language, a novel seems almost like total randomness, but the rules of spelling, grammar, and narrative introduce an element of order.

B

The Problem of Uniqueness: I often have a certain reaction to a lot of generative art. When generative art creates infinite variations on something, each individual thing seems to lose its impact. You end up going "cool" then moving on. I feel like the stuff that works for me is when the objects generated are not presented as the main event. The generating system is the unique object with the unique experience.

Zapra – LookingOutwards02

Mosaic Virus by Anna Ridler (2019)

Extrapolating on the "tulip fever" craze in 17th century Netherlands, Anna Ridler's installation,"Mosiac Virus," uses AI technology to develop stunning videos of synthetic tulips. In the real tulip industry, collectors value the flowers for uniqueness, viruses and mutations. Riddler highlights these prized features with her generated tulips; their unique mutations growing, blooming and adapting to the rise and fall of the bitcoin market. The project began with her searching for, photographing, and categorizing ten thousand tulips by hand, which became its own installation seen here. She then fed a generative adversarial network (GAN) these ten thousand photographs as a training set for her own creations. I find this supplementary installation equally, or perhaps even more, important than the project itself. When ownership of generative art is challenged, I question whether work generated with the photos or paintings of others can truly be considered theirs. With this training set however, Ridler creates wholy individual work that calls attention to the human labor that goes into creating generative, "autonomous" art. I feel that her work manages to capture the stunning nuances of a biological organism that organically encapsulates effective complexity.

Myriad (Tulips) by Anna Ridler (2019 ), the hand-photographed and categorized training set for Mosaic Virus

DSC01053.JPG

Sources:

HyperAllergic

Annaridler.com

sovid – Looking Outwards 02

 

This week I chose to focus on Leonardo Solaas's work shown at "La emergencia de la imagen" ("The Emergency of Image"), the final show for the Production Marathon Lab 2016 at the Spain Cultural Center in Buenos Aires. Working together with a group of 16 participants, the artist used generative systems to create random and minuscule porcelain sculptures, each with a unique and recognizable body, personality, and/or function. I couldn't find information on whether or not these sculptures were 3D printed or hand-modeled after being generatively designed, but either way I love how a mass society of small beings can be produced with technology.

Click the images below to go to his portfolio.

La emergencia de la imagen

La emergencia de la imagen

sovid – Reading 02

1A. I think any board game that creates a complex world based on a set of rules can be considered a work with effective complexity. A family favorite of mine is the German kingdom building game Carcassonne. The game relies on a series of very specific rules and outcomes for each draw of the game, yet every time it is played, the kingdom looks entirely different, as each tile placed is drawn at random.

Related image

1B. The issue of intent in generative art is very interesting to me because I (whether I try to or not) tend to lean towards labor heavy work and attribute more value to something that has been painstakingly created. While happy accidents are something I frequently stumble upon, I can't help but think of them as a lazy approach and give less importance to a work.

tli-Interruptions

Observations
  1. The piece is square.
  2. The piece shows black lines on a white background.
  3. The black lines are the same length.
  4. The black lines are rotated randomly.
  5. The black lines are approximately arranged in a grid.
  6. Some black lines are removed from the grid in patches.
Results

https://editor.p5js.org/helveticalover/sketches/6cTRH1cfC

Process

Deriving an implementation from the observations I listed above were fairly simple. I wrote an algorithm to place lines arranged in a square grid, rotate the lines by a random angle between 0 and 180 degrees, and culled lines that were located in a cell above some threshold for Perlin noise. The trickiest part of knowing how to implement this algorithm was thinking of a way to remove "patches" of lines rather than random cells, but this was solved once I remembered Perlin noise. After the implementation came tuning parameters to imitate Molnár's original. I tuned the number of lines, the length of the lines, the stroke weight of the lines, the scale of the Perlin noise, and the threshold for culling lines. The last two parameters in particular were trickiest because Interruptions displays a very specific frequency and distribution of removed "patches". Too many or too few interruptions, as well as too large or too small interruptions, would drastically change the appearance of the piece. In the interest of replicating Interruptions as closely as possible, I spent the most effort tuning these variables.

ilovit-Interruptions

Observations:

  1. The artwork is square.
  2. The artwork consists of many short black lines, on a white background.
  3. The lines all have the same length.
  4. The lines directions vary
  5. The lines tend vertical
  6. The lines are in a grid
  7. The grid is interrupted intermittently by white space
  8. The interruptions tend to group in larger blobs
  9. The distances between the centers of the lines is half the length of the lines
  10. The grid is 56x56
  11. The lines are thin and black
  12. The background is white

Interruptions Recode:

https://editor.p5js.org/ilovit/sketches/xFpvWLjAW

Reproducing the shape of the work was easy. I got the lines the right length and at the right intervals pretty quickly, and once some random element was introduced to the angles, the picture looked very reminiscent of Molnar's work. figuring out that I should use Gaussian distribution to get the lines pointing mostly vertically but still randomly also took a short amount of time. However, the titular interruptions were very difficult to reproduce and I don't think I quite succeeded. I tried to create the interruptions using just the random function. My method was thus: I had each line look at the lines around it to decide how likely it was to disappear, then I spent a really long time futzing with the various numbers to try to get it to look a little more like Molnar's piece.