Looking back to data, we can see if the consequences are plausible; looking forward to theory, we can see if general principles are suggested.

Looking back to data, we can see if the consequences are plausible; looking forward to theory, we can see if general principles are suggested.

Holland's and Kauffman's work, together with Dawkins' simulations of evolution and Varela's models of autopoietic systems, provide essential inspiration for the new discipline of artificial life, This approach, initiated by Chris Langton (1989, 1992), tries to develop technological systems (computer programs and autonomous robots) that exhibit lifelike properties, such as reproduction, sexuality, swarming, and co-evolution.

The measure of performance of any given agent is the amount of money it accumulates through its actions.

If we are to understand the interactions of a large number of agents, we must first be able to describe the capabilities of individual agents.

The recycling of resource by the aggregate behavior of a diverse array of agents is much more than the sum of the individual actions.

With theory, we can separate fundamental characteristics from fascinating idiosyncrasies and incidental features. Theory supplies landmarks and guideposts, and we begin to know what to observe and where to act.