Like a process, an autonomous agent is a set of rules representing a component part of a natural system. However, an agent has two important differences from a process - where it lives and how it communicates. We define an environment to be an artificial representation of this space. Our autonomous agents can perform the activities defined by their computer program in this environment. This sense of environment does not exist in a process based simulation.
Processes are only aware of themselves and the resources they wish to acquire.
With Multi-Agent simulation the environment is independent of the agents within it. In order to simulate a natural system with its full complexity of interacting parts, we must define exactly how the agents communicate with each other. This communication can be anything from a rule saying that predator meeting a prey implies the prey is dead to the dance of the honey bee directing the foraging activities of other bees. This makes Multi-Agent simulation an extremely powerful tool but one which is hard to verify in the context of known mathematical theory. In many ways multi-agent simulations are a lot less rigorously defined than process based simulations.