Organic formations
- Edge of chaos
A computer follows rules. At each moment, the rules determine exactly what the computer will do next. We say that a computer is an example of an automaton. Other, simpler examples of automata also exist.These more abstract rule-following devices can be easier to study computers, and they can be interesting to study in their own right. One type of automaton that has received a lot of attention is cellular automata.For one thing, they make pretty pictures. For another, they are related to exciting new ideas such as artificial life and the edge of chaos. Here is a fairly simple example.
- Parallel cellular machines
Nature abounds in systems involving the actions of simple, locally-interacting components, that give rise to coordinated global behavior. These collective systems have evolved by means of natural selection to exhibit striking problem-solving capacities, while functioning within a complex, dynamic environment. Employing simple yet versatile parallel cellular models, coupled with evolutionary computation techniques, this volume explores the issue of constructing man-made systems that exhibit characteristics such as those manifest by their natural counterparts. Parallel cellular machines hold potential both scientifically, as vehicles for studying phenomena of interest in areas such as complex adaptive systems and artificial life, as well as practically, enabling the construction of novel systems, endowed with evolutionary, reproductive, regenerative, and learning capabilities. This self-contained volume examines the behavior of such machines, the complex computation they exhibit, and the application of artificial evolution to attain such systems.
- oneDautomata
This is a 1 Dimensional Cellular Automata simulator. You can play with the rule set by clicking on the boxes at the lower left, and play with the initial population by clicking on the boxes at the lower right.
Chaos
- Chaotic pendulum
This applet contains 2 double pendula mounted at the same pivot point. One pendulum is blue and the other one is black. Initially, the black pendulum is hidden by the blue one.The starting positions of the pendula are different by a very small amount. Start the applet and observe that the pendula start to diverge after about 30 seconds.
Randomness
- Algorithmic image gallery
A great collection of algorithmic images. You can also find the source code.The navigation is a bit complicated, so read the instructions on the page to enjoy endless number of dynamically generated images.
Complexity
- Concepts of complexity
A paper on Complexity and Complex systems.
L-Systems
- ISYS
This thing lets you evolve L-Systems in 2D. You have 9 L-Systems. Click on one to center it and generate 8 children. The children vary in Axiom, Transform, initial color and color vector. If you don’t like any of the children, click the middle to generate more.
Symmetry & Tiling
- Gumowski-Mira applet
Great rendering of the Gumowski-Mira formula.
Artificial Life
- Steering behaviour
This paper presents solutions for one requirement of autonomous characters in animation and games: the ability to navigate around their world in a life-like and improvisational manner. These “steering behaviors” are largely independent of the particulars of the character’s means of locomotion. Combinations of steering behaviors can be used to achieve higher level goals (For example: get from here to there while avoiding obstacles, follow this corridor, join that group of characters…)This paper divides motion behavior into three levels. It will focus on the middle level of steering behaviors, briefly describe the lower level of locomotion, and touch lightly on the higher level of goal setting and strategy.
- Particle tree
This applet demonstrates how recursion and randomness can simulate natural patterns such as the branches of a tree or the paths of particulates in the air. A good applet to study for beginning programmers. Code also available on the site.
- Frog queue
We cannot figure out what frogs are thinking of, so that we cannot predict which direction a frog will move to. In this applet, a frog queues for another frog who is the nearest and has similar direction of movement. A frog who can’t find the target one to queue for makes itself red and bigger figure. A frog who is in a queue occasionally deviate from it so he acquire the freedom to do what he wants.
- Evolve
The green dots are food. The magenta dots are critters. The critters eat the food. When a critter eats enough food, it reproduces. Its child is almost exactly like it except that its genetic movement pattern is just slightly different. A nice little interactive simulation where you can manipulate the food distribution and growth rate etc.
- Langston’s Ant
Langston’s Ant is a simple algorithm consisting of the following two rules:* If the ant is on a black dot, paint it white and go right.
* If the ant is on a white dot, paint it black and go left.This applet starts the ant out in a box of randomly generated “dirt.” It’s pretty entertaining to watch the ant scoot around and muddle things up indefinitely, to no avail. Poor guy. You can restart the ant display (with freshly generated dirt!) by pressing the space bar while the mouse cursor is inside the applet box.
- uncontrol
Visual experiments based on dynamic motion & interaction. Using simple elements line lines, curves, circles and squares Manny has created some engaging and rich experiences.
- A-Life
ALife–Artificial Life–uses a simulated real-life environment to solve an engineering problem. ALife innovations have been responsible for breakthroughs in architecture, medicine, ecology, meteorology, biology, and other sciences. Artificial intelligence, one of ALife’s most promising areas of research, probably played a big part in designing your computer. Using several Java applets, you can play the Game of Life with live cells and dead cells, discover Boids Swarm, and learn about fuzzy logic.
