Author: bb3621

Concept

For this project, I created a random walker that moves using dynamic probabilities instead of fixed directions. At every step, the walker makes a decision: it has a 50% chance to move toward the mouse and a 50% chance to move in a random direction. This creates motion that sometimes feels intentional and sometimes unpredictable.

To connect motion to another medium, I mapped movement into color by letting the walker walk through HSB color space. As the walker moves, its hue slowly shifts, leaving a trail of changing colors. This makes the motion visible not only through position, but also through color.

Code Highlight

The part I am most proud of is the simple probability rule that controls the walker’s behavior:

// 50% chance: move toward mouse
if (random(1) < 0.5) {
  let target = createVector(mouseX, mouseY);
  let dir = p5.Vector.sub(target, pos);
  dir.setMag(step);
  pos.add(dir);
} 
// 50% chance: random move
else {
  let angle = random(TWO_PI);
  pos.x += cos(angle) * step;
  pos.y += sin(angle) * step;
}

With only one small decision, the system creates two very different behaviors: attraction and randomness. This balance makes the motion feel alive without being complicated.

Embedded Sketch

Reflection and Future Work

This project showed me how simple rules can create expressive motion. Even with only two possible choices, the walker feels responsive and unpredictable at the same time. I also liked how color helped reveal the path and rhythm of the movement.

In the future, I would like to change the probability based on the distance to the mouse so the attraction becomes stronger or weaker depending on position. I would also like to add multiple walkers with different behaviors and experiment with Gaussian step sizes to create smoother motion. Another idea is to map movement to sound, such as pitch or stereo pan, instead of color.

Overall, this project helped me understand how probability and interaction can shape motion in simple but interesting ways.

 

While reading the introduction of The Computational Beauty of Nature, I realized that the author is challenging the way we usually try to understand systems. We often break things into smaller parts, but Flake explains that this is not enough to explain how complex behavior appears. Even if we understand each part well, we still may not understand what happens when many parts interact together. This idea changed the way I think about learning and problem solving.

The example of ants stood out to me the most. A single ant behaves in a simple way, but together ants form organized colonies with complex behavior. I found this interesting because it shows that complexity does not need complicated rules. It can come from simple actions repeated many times. This reminded me of programming, where small pieces of code can create systems that behave in surprising ways.

I also liked the idea that nature itself “computes.” Systems react to their environment, adapt, and evolve over time. Seeing learning and evolution described in this way made me realize that computer science is connected to many other fields, not just technology.

Overall, this chapter made me more curious about how simple rules can lead to complex behavior, and it helped me see computation as a way to understand patterns and intelligence in the world, not only as something done by machines.