The Vinod Wadhawan Blog: 77. Artificial Life

With the advent of artificial life, we may be the first creatures to create our own successors. . . If we fail in our task as creators, they may indeed be cold and malevolent. However, if we succeed, they may be glorious, enlightened creatures that far surpass us in their intelligence and wisdom. It is quite possible that, when conscious beings of the future look back on this era, we will be most noteworthy not in and of ourselves but rather for what we gave rise to. Artificial life is potentially the most beautiful creation of humanity (Doyne Farmer and Alletta Belin).

http://www.metafysica.nl/a_life.html

Christopher Langton is the main originator of the subject of artificial life. The term artificial life (AL, or Alife) was coined by him around 1970: AL is ‘. . an inclusive paradigm that attempts to realize lifelike behaviour by imitating the processes that occur in the development or mechanics of life.’

In the more familiar field of artificial intelligence (AI) one uses computers to model neuropsychology. Likewise, in the field of AL one uses computers to model the basic biological mechanisms of evolution and life (Heudin 1999). In abstracting the basic life processes, the AL approach emphasizes the fact that life is not a property of matter per se, but the organization of that matter. The laws of life must be laws of dynamical form, independent of the details of a particular carbon-based chemistry that just happened to arise here on Earth. It attempts to explore other possible biologies in new media, namely computers and robots.

http://www.cs.ucla.edu/~dt/alife.html

The idea is to view life-as-we-know-it in the context of life-as-it-could-be. There was a recent report of how Lee Cronin of the University of Glasgow could create lifelike cells out of metal.

In conventional biology one tries to understand life phenomena by a process of analysis: We take a living community or organism, and try to make sense of it by subdividing it into its building blocks. By contrast, AL takes the synthesis or bottom-up route. We start with an assembly of very simple interacting units, and see how they evolve under a given set of conditions, and how they change when the environmental conditions are changed.

One of the most striking characteristics of a living organism is the distinction between its genotype and phenotype. The genotype can be thought of as a collection of little computer programs, running in parallel, one program per gene. When activated, each of these programs enters into the logical fray by competing and/or cooperating with the other active programs. And, collectively, these interacting programs carry out an overall computation that is the phenotype. The system evolves towards the best solution of a posed problem.

By analogy, the term GTYPE is introduced in the field of AL to refer to any collection of low-level rules. Similarly, PTYPE means the structure and/or behaviour that results (emerges) when these rules are activated in a specific environment.

What makes life and brain and mind possible is a certain kind of balance between the forces of order and the forces of disorder. In other words, there should be an edge-of-chaos existence. Only such systems are both stable enough to store information, and yet evanescent enough to transmit it.

Life is not just like a computation; life literally is computation. And once we have consciously made a link between life and computation, an immense amount of computational theory can be brought in. For example, the question ‘Why is life full of surprises?’ is answered in terms of the undecidability theorem of computer science, according to which, unless a computer program is utterly trivial, the fastest way to find out what it would do (does it have bugs or not?) is to actually run it and see. This explains why, although a biochemical machine or an AL machine is completely under the control of a program (the GTYPE), it still has surprising, spontaneous behaviour in the PTYPE. It never reaches equilibrium, and there is perpetual novelty.

The computational aspect of the AL approach invokes the theory of complex dynamical systems (Wadhawan 2010). Such systems can be described at various levels of complexity, the global properties at one level emerging from the interactions among a large number of simple elements at the next lower level of complexity. The exact nature of the emergence is, of course, unpredictable because of the extreme nonlinearities involved.

Here are some websites devoted to artificial life:

Life arose from an interplay of the blind forces of Nature, with one thing leading to another. There was no 'Designer' involved. In 1986 Richard Dawkins published his famous book The Blind Watchmaker. The book also had the Blind Watchmaker Applet. The computer code mimics Nature's power of cumulative Darwinian natural selection in the evolution of life. Of course, it is not possible to simulate all the complex interactions at work in a real system in Nature. But the applet catches the essence of the processes by introducing slight variations in each generation of the population, the 'selection' being determined by the whims and fancies of the user. Here is a sampling of the kind of 'biomorphs' that get 'created':