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.


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.

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.


  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.


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.



  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:

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.


Question 1A.

I think games with very simple rules that are played by humans are a good example of effective complexity because they are great stages for emergent interactions. Games that come to mind are the loop activity we did in class and r/place, where a rule as simple as "You can color a pixel every 20 minutes" allows for complex social interactions. I choose these as examples because they are a combination of order (simple rules) and disorder (human individuality) that constitute a complex system. Perhaps the only point of contention is whether these examples are truly generative, because the artist(s) are not removed from the decision-making in the way that Galanter emphasizes in the beginning of the text.

Question 1B.

I relate the most to the problem of meaning because I find it something that I struggle with in all forms of art. Galanter highlights generative art's inclusiveness of all forms of "meaning", whether it be presenting the system itself, invoking awe, or delivering social commentary. Because of this, I find it hard in general to evaluate the critical value of my ideas. At the same time, I find it liberating to not have to evaluate the critical value of my ideas because all delivered meanings are valid within the realm of generative art, including the lack of "higher" meaning beyond being interesting. Galanter also mentions a radically bottom-up "truth-to-process" approach, which I find intriguing but also personally difficult to practice. As an artist, I enjoy adopting a director position over my projects, which makes it difficult for me to relinquish control to the system.


1A. Going back to teamLab once again, I believe their piece BORDERLESS exhibits a high effective complexity. The experience of the art itself is completely different for every viewer, as the programs and displays are almost completely interactive, depending almost entirely on user input and movement. It sits in the middle of total order and total randomness, because the art generated is created by the same algorithm (total order), but the art's conveyance and comprehension is different for everyone (total randomness). 


1B. Problem of Authorship:

I took the mini-course Art & Arduino last year, where I thought about this specific idea for a long time, because my final project dealt with a robot producing art based off of human input. Especially since I am a digital artist interested in computer graphics and animation, this problem is very close to the career I want to pursue. I came to believe that yes, since the artist is the one creating the program and coding the processes that the system uses to generate the art, the authorship of the artwork can be credited to the artist and not the machine. If the artist is simply using specific programs of the machine and changing the input values to vary results, then by the transitive property, the artist is effectively creating the artwork itself as well.

MoMar – Reading02

Cities that have been around since the middle ages are prime examples of effective complexity. In the olden days, urban planning was not widely used so people typically built buildings where they wanted to. On the scale between total randomness and total order, it's around the middle because as time progresses, the city gets more organized. There is a clear division between the two with the wide road surrounding the old city.


Zapra – Interruptions

View code

Observations / Assumptions:
  1. The image is a white square with black lines
  2. There are many short lines of the same size
  3. There are seemingly random gaps in the lines
  4. The lines form a matrix of rows and columns
  5. The lines are centered around a midpoint of equal distances apart
  6. Most lines are angled left or right, but have a slight proclivity towards the vertical
  7. There are often several gaps in the image of different sizes
  8. Some gaps extend or go over the edge of the grid
  9. There are about 60 lines in each row
  10. The space between each row is less than the length of the lines (if all lines were vertical, they would overlap about halfway)

Some of frustration I ran into with this project was based off an incorrect assumption I made about how the lines were drawn. I had assumed all the lines were spaced equally based on the top endpoint rather than middle. Once I realized this, I struggled to find an effective way to center all the points around these midpoints (but once I did, I audibly yelled "YES!" alone in my apartment and gave myself a high five). I haven't done much in-depth coding since last year, so as I've progressed with this assignment I'm starting to remember more and more. I think ideally I could still tidy up my code, but I at least feel satisfied with the end result.

Some previous versions:


1a. An Example of Effective Complexity

The human brain is biased towards total order: many rules governing brain organization lead to strong similarity between brains. These rules govern how neurons will be constructed, and how they will be linked together in patterns of excitation and inhibition that ultimately give rise to predictable output, e.g. the same(-ish) perception given a constant stimulus. But a brain with too much order could accomplish no more than an 80's-era AI expert system. The formation of unique memories in a newly-formed, 'blank slate' brain (which leads to learning) could be seen as an expression of chaos within the orderly system.

1b. The Problem of Meaning

Can and should generative art be about more than generative systems?

This problem is particularly conflicting to me because I'm interested in the mistakes that come out of a generative process. I like things that didn't come out as intended, like a GAN-bred puppy with three eyes. In that way I am interested in generation itself, how mutations are introduced, and how society turns against these unfortunate 'failed' instances of an algorithm. But, unlike the 'purity' of the process  Galanter describes, where the artist has no particular goal in mind, I am always obsessing over making exactly what I wanted to make. Ideally, I would want generative art that I make to reach a point between the purely generative sublime and the dirty, ordinary world of meanings and signs.

lubar – Interruptions


  1. The artwork is a square
  2. The centers of each line segment are in a grid form
  3. The line segments appear randomly rotated
  4. The line segments occasionally intercept
  5. There appear to be 57 possible lines across each axis
  6. The piece has a blank margin
  7. There are clusters of blank spaces that appear in random locations
  8. The clusters of black spaces are not uniform in size or shape
  9. The length of each line is slightly less the double the distance between each line
  10. The lines are thin and short

Interruptions Sketch Link

In the process of creating this, I found the rotation of the line segments to be particularly frustrating, although I initially assumes that that would pose the least challenges. The method that I was using involved the rotate() and translate() functions and it took me a while to figure out to use multiple translations I needed push() and pop(). Overall however, especially after discussing Perlin noise a bit with Sophia, I found the other elements to run smoothly, although not perfectly when compared with the original pieces. Molnar's original interruptions have a slightly 'free-er' quality that I was not able to capture despite playing around with it for a long time. Despite the slightly denser interruptions, I am content with how the reproduction turned out, and I would be curious to know how that effect was/might have been achieved without Perlin noise, as I haven't quite been able to wrap my head around it yet.