A Multi-Agent System is a distributed system where the agents or nodes
perform complex functions that cannot be written down in analytic form.
Multi-Agent Systems are highly connected, and the information they contain is
mostly stored in the connections. When agents update their state, they take
into account the state of the other agents, and they have access to those
states via the connections. There is also external, user-generated input into
the Multi-Agent System. As so much information is stored in the connections,
agents are often memory-less.

A key challenge in modern computing is to develop systems that address
complex, dynamic problems in a scalable and efficient way, because the
increasing complexity of software makes designing and maintaining efficient and
flexible systems increasingly difficult. Biological systems are thought to
possess robust, scalable processing paradigms that can automatically manage
complex, dynamic problem spaces, possessing several properties that may be
useful in computer systems.

A primary motivation for research in Digital Ecosystems is the desire to
exploit the self-organising properties of natural ecosystems. Ecosystems arc
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties have not been made explicit in Digital Ecosystem research.
Here, we introduce how biological properties contribute to the self-organising
features of natural ecosystems.