the old, analytic way is replaced by new, synthetic one.

the old, analytic way is replaced by new, synthetic one.

A : Let's take an ecosystem - like a jungle for example. When you try to approach it, when you study an ecosystem, using top-down approach, you start with an ecosystem as a whole and then you begin dissecting it until you get to the final units, which are the animals and the plants. That is the method that science has used for 400 years now and it's called analysis or top-down analysis. The problem is that many of the properties of an ecosystem rise from the interaction between the animals - for instance the interaction between the predators and the preys, the parasites and hosts or between simbiots. When you dissect things and take them apart, the first thing you lose is these interactions. You reach the final units by dissecting things, but then at the end you end up with units that are separated from each other. In an ecosystem, society or any other system, many of the properties are what is called synergetic or synergistic properties, that are more than the sum of the parts. But when you do analysis, you end up with a bunch of units and then you want to add them up - everything that was more than the sum gets lost - almost by definition.

So, to complement analysis, we need synthesis, and that's what artificial life does. In artificial life, you do not analyze an ecosystem, you synthesize it. I we begin with several populations of virtual animals inside a virtual environment and set them to interact with each other, the synergistic properties of an ecosystem emerge from those interactions. So instead of using top-down, starting at the top of the whole ecosystem and working your way down to the animals and the plants, you start with the animals and the plants - at the bottom - and work your way up. The advantage is that you do not lose the properties of interactions because you created these virtual animals and put them together to interact with each other. So, an ecosystem should emerge from those interactions.

Another example would be a flock of birds or an insect colony. In an insect colony, the whole colony has a kind of swarm intelligence. The colony as a whole is kind of like a computer. One little ant finds food and then the others follow him as if the whole colony was an intelligent being. Or if you have a flock of birds - there are a few rules when flying ; keep the same speed as the bird next to you, if you're too close get farther away and if you're too far away, get closer. With those few rules - as long as you put enough birds together - flock behavior emerges. And the whole flock has a kind of gracefulness of its own. That is more than the sum of its parts, it's more than the sum of the birds.

Manuel De Landa and Karlo Pirc (Interviewer)