Artificial life (commonly Alife or alife) is a field of study and an associated art form which examine systems related to life, its processes, and its evolution through simulations using computer models, robotics, and biochemistry.[1] The discipline was named by Christopher Langton, an American computer scientist, in 1986.[2] There are three main kinds of alife,[3] named for their approaches: soft,[4] from software; hard,[5] from hardware; and wet, from biochemistry. Artificial life imitates traditional biology by trying to recreate biological phenomena.[6] The term "artificial life" is often used to specifically refer to soft alife.[7]
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Artificial life studies the logic of living systems in artificial environments. The goal is to study the phenomena of living systems in order to come to an understanding of the complex information processing that defines such systems.
Also sometimes included in the umbrella term Artificial Life are agent based systems which are used to study the emergent properties of societies of agents.
While life is, by definition, alive, artificial life is generally referred to as being confined to a digital environment and existence.
The modeling philosophy of alife strongly differs from traditional modeling, by studying not only “life-as-we-know-it”, but also “life-as-it-might-be”.[8]
In the first approach, a traditional model of a biological system will focus on capturing its most important parameters. In contrast, an alife modeling approach will generally seek to decipher the most simple and general principles underlying life and implement them in a simulation. The simulation then offers the possibility to analyse new, different life-like systems.
Red'ko proposed to generalize this distinction not just to the modeling of life, but to any process. This led to the more general distinction of "processes-as-we-know-them" and "processes-as-they-could-be" [9]
At present, the commonly accepted definition of life does not consider any current alife simulations or softwares to be alive, and they do not constitute part of the evolutionary process of any ecosystem. However, different opinions about artificial life's potential have arisen:
This is a list of artificial life/digital organism simulators, organized by the method of creature definition.
| Name | Driven By | Started | Ended |
|---|---|---|---|
| Tierra | executable dna | early 1990s | ? |
| Avida | executable dna | 1993 | NA |
| Evolve 4.0 | executable dna | 1996 | 2007 |
| Darwinbots | executable dna | 2003 | |
| Framsticks | executable dna | 1996 | NA |
| breve | executable dna | 2006 | NA |
| DigiHive | executable dna | 2006 | 2009 |
| TechnoSphere | modules | ||
| Creatures | neural net | ||
| Noble Ape | neural net | ||
| Polyworld | neural net | ||
| AnimatLab | neural net | 2009 | |
| 3D Virtual Creature Evolution | neural net | NA |
These contain organisms with a complex DNA language, usually Turing complete. This language is more often in the form of a computer program than actual biological DNA. Assembly derivatives are the most common languages used. Use of cellular automata is common but not required.
Individual modules are added to a creature. These modules modify the creature's behaviors and characteristics either directly, by hard coding into the simulation (leg type A increases speed and metabolism), or indirectly, through the emergent interactions between a creature's modules (leg type A moves up and down with a frequency of X, which interacts with other legs to create motion). Generally these are simulators which emphasize user creation and accessibility over mutation and evolution.
Organisms are generally constructed with pre-defined and fixed behaviors that are controlled by various parameters that mutate. That is, each organism contains a collection of numbers or other finite parameters. Each parameter controls one or several aspects of an organism in a well-defined way.
These simulations have creatures that learn and grow using neural nets or a close derivative. Emphasis is often, although not always, more on learning than on natural selection.
Hardware-based artificial life mainly consist of robots, that is, automatically guided machines, able to do tasks on their own.
Biochemical-based life is studied in the field of synthetic biology. It involves e.g. the creation of synthetic DNA. The term "wet" is an extension of the term "wetware".
Alife has had a controversial history. John Maynard Smith criticized certain artificial life work in 1994 as "fact-free science".[11] However, the recent publication of artificial life articles in widely read journals such as Science and Nature is evidence that artificial life techniques are becoming more accepted in the mainstream, at least as a method of studying evolution.[12]
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