Several (eusocial) societies show the ability to react (as a total) in plasticity, to organize themselves dynamically and efficiently and to make decisions
If these processes are
- made in parallel
- following decentralized processes
- done without hierarchical decision making structures
- not involving a special “pre-made” plan (given from outside or being derived from the past)
- not enforced from outside to happen (decide or organize) in that way (e.g. special source-produced odors leading animals to a specific food source)
then we can call the phenomenon “self-organization”.
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One way to deal with this topic is to simulate the processes with a computer by creating a multi-agent simulation (=MAS). In a MAS you create the behavioral
program for a single actor (=agent) not from a global but from an individual point of view. This means, you write a program that collects the sensory input of an actor, that decides the next action of the actor
(based on the current input, the memory, the current state and the current goals and plans) and finally executes this action. In this way, there is no global program that maybe already (directly or indirectly)
implements a group behavior. If you find a similar group behavior in your simulation (by letting hundreds of these single individual programs run) as you can observe it in nature, you have found a set of individual
behavioral rules that is able to reproduce the natural group behavior. But beware, this could be only one set of individual behaviors, there might be others ...
If you want to learn more about self organization and MAS, please refer to the following books:
- Camazine S., Deneubourg J.-L., Franks N.R., Sneyd J., Theraulaz G. and Bonabeau E. (2001) Self-Organization in biological systems. Princeton
- Bonabeau E., Dorigo M. and Theraulaz G. (1999) Swarm intelligence. From natural to artificial systems. Santa Fee Institute studies in the
sciences of complexity. Oxford University Press.
- Resnick M. (2000) Turtles, termites and traffic jams. MIT Press.