Archive for the ‘artificial life’ tag
Electric sheep
Electric Sheep is a collaborative abstract artwork founded by Scott Draves. It’s run by thousands of people all over the world, and can be installed on any ordinary PC or Mac. When these computers “sleep”, the Electric Sheep comes on and the computers communicate with each other by the internet to share the work of creating morphing abstract animations known as “sheep”. The result is a collective “android dream”, an homage to Philip K. Dick’s novel Do Androids Dream of Electric Sheep.
Anyone watching one of these computers may vote for their favorite animations using the keyboard. The more popular sheep live longer and reproduce according to a genetic algorithm with mutation and cross-over. Hence the flock evolves to please its global audience. You can also design your own sheep and submit them to the gene pool.
More information:
The Electric Sheep Screen-Saver: A Case Study in Aesthetic Evolution (pdf)
Source code at Source Forge
Electric Sheep Wiki
Artificial Evolution for Computer Graphics, Karl Sims
BodyLab Researching the evolution of the human body shape
Algorithmic Botany
I ‘ve been re-reading ‘Out of Control, The Biology of Machines’ and took some time to look up some of the people mentioned who are creating virtual plant life.
If you are interested in creating plants for artificial worlds, or to use to study botany you’ll want to start with the Algorithmic Botany website. There are tons of papers you can download, a book ‘The Algorithmic Beauty of Plants’ and every thing you need to know about ‘cpfg’ the Plant and Fractal generator with Continuous Parameters. Which is a program you can use to generate your own plants using the L-system ( Lindenmayer System ).
If you’d like to dig into the L grammar itself as well as generate plants check out GroIMP, open source Java 3D software for modeling growth grammars.
More information:
Wikipedia, L-system
An interesting swarm algorithm based on bats
Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems. In this paper, we propose a new metaheuristic method, the Bat Algorithm, based on the echolocation behaviour of bats. We also intend to combine the advantages of existing algorithms into the new bat algorithm. After a detailed formulation and explanation of its implementation, we will then compare the proposed algorithm with other existing algorithms, including genetic algorithms and particle swarm optimization. Simulations show that the proposed algorithm seems much superior to other algorithms, and further studies are also discussed. [download the paper pdf]
More information
Other swarm papers by Xin-She Yang
