Just as artificial intelligence comes in several philosophically distinct flavors—for instance, Strong versus Weak—the discipline of artificial life can encompass a number of things, from the pragmatic use of computer simulation to explore principles of biological self-organization to meaning exactly what it says: artificial life. This chapter describes some of the factors that have motivated attempts to replicate living or lifelike processes and discusses the interplay between "design" and "emergence."

Water, like any scarce common resource, creates competition that can lead to conflict, but, as Wendy Barnaby concludes in her Essay, wars are not waged over water (see Nature 458, 282–283; 2009).

As software complexity grows (which it inevitably does), the problems of managing that complexity grow exponentially. Nowhere is this more significant than in AI, where we are attempting to emulate some of the most sophisticated and complex forms of behavior. It is a reasonable assertion that intelligent systems cannot be simplified-that their behavior is necessarily a result of their immense complexity. If we are to make intelligent computer programs, they must be complex. If that complexity exceeds our ability to manage it by conventional top-down modes of thought, then we must find another way. To do this, we need to understand how anarchy works. One of the largest anarchies on the face of this planet is your own body. Perhaps the most striking feature of complex organisms is their cellularity. A cell's most significant feature is its membrane. The membrane's purpose is to keep the outside out and the inside in. Modern software uses a similar concept to isolate components from each other, through the object-oriented programming methodology. In many respects, the biological concept of cellularity is applicable to computer software, especially if you have a predilection for designing bottom-up, massively parallel simulations for creating intelligent artificial life-forms.

Why do we create neural networks that have no chemistry? Why simulate genetics without a digestive system? There is no such thing as half an organism, yet most attempts to generate intelligent or life-like agents are based essentially on a single mechanism. Granted, a few people are working on evolvable neural networks, but the genetics is seen as a means to an end, rather than a part of an integrated, heterogeneous system. Neural networks themselves are generally homogeneous entities, too-one kind of neuron, interconnected in one or at most a few different ways and performing a single task. Yet, we know that our brains are not like that at all: they are divided into regions that perform many different tasks and contain populations of very different cells. What is more, artificial neural networks generally employ only direct synaptic connections for their signal paths, despite our awareness that real brains are swimming in neurotransmitters that have diffuse and plural functions. Taking a holistic approach and attempting to create such a “whole” organism might sound like a brave or even foolhardy task. However, in this article, I explore the possibilities and see what could be done