In a universe describing natural phenomena for instance, each component is subject to nonlinear modifications during time. Modifications affect both agents' data and behaviour. Two kinds of dynamic evolution could be considered: modification of the structure by re-organisation of the acquaintances network or modification of behaviour.
The first one constitutes a fundamental feature in complex systems modelling, and is often called self-organisation. Indeed, this property allows a system to be simulated without any initial constraints. The network is then organised as events arrive, until the system hits a critical state. In most natural systems, the critical state is the most favourable state to observe global phenomena. This part of the work is beyond the scope of this paper.
The modification of behaviour is a fundamental notion for an agent. This
characteristic authorises an agent to reproduce adequate behaviours - that is,
those behaviours most adapted to his environment and the current situation.
Multi-agent systems typically are of considerable complexity with respect to
both their structure and their functionality. It is extremely difficult to
correctly determine when and why a behaviour of an agent or an activity of a
multi-agent system occur at the time of its design. This kind of problem can
be reduced by giving the agent the ability to adapt himself to new situations.
This feature will be called self-adaptation so far. Self-adaptation is
then defined as self-modification that enables a system to survive in a changed
environment [9]. Understanding the reasons for which behaviours emerge is often
surprising and seen as a kind of "magic phenomenon" in multi-agent systems [1].
Nevertheless, emerging behaviours are the result of interactions and situations
of co-operation between underlying agents in the architecture. Co-operation
between agents encourages emerging behaviours, because collective agents' works
could make an action possible.