What do we need for implementing emergence?
a set of active agents,
a (set of) communication mechanism(s),
a common goal the agents implicitly or explicitly share,
cooperation strategies of agent (optionally),
a method to determine when to stop (optionally).
The agents are active in that they execute some functionality in order to reach a goal or subgoal. They communicate with other agents to transfer information. And they recognize when their work is done or when they should stop.
There is a lot of possible variation here:
Agents might all share the same role (behavior) or they may have different roles.
Agents might be organized in a peer-to-peer fashion or hierarchically.
Agents might share the same goal or have individual or role-based goals.
Control might be distributed across all agents, or only be assigned to one or a multiple of them.
Agents might be preinstantiated at start-up or adapt their number or roles according to environmental conditions or achievement (being born, living, dying).
Agents might be able to give life to new agents. They may also be able to terminate other agents, even themselves.
There even could be some environmental conditions that result in death or birth of agents.
Communication might be one-to-one or one-to-many or abide to any other message exchange pattern.
Communication might be synchronous or asychronous.
Agents might adapt their behavior including communication due to environmental changes or interaction with other agents.
Which implies, the environment might change.
Agents might "move" in their environment.
There could also be diverse neighbor environments.
In a Map-Reduce system we have a controlling agent and subordinate agents. The controlling master might instantiate slaves depending on problem complexity. Goal of the system is to reach a common goal such as finding all specific entities in an environment. The master communicates with the slaves and provides a subgoal to each of them. The slaves solve the subgoal and may act as masters for their subgoal, thus recursively applying the pattern. Slaves send their findings back to their master which then recombines partial results to the common result.
In Leader-Followers, the leader is always the controlling agent. When it receives an information from its environment, it promotes a follower to become the leader, and switches its role to worker. A worker who is done with a job, switches its role into follower and enters the followers list.
All these systems reveal emergent behavior. And this also resembles swarms like ant populations. There are different roles such as queen, warrior, worker, etc. The population's goal is to sustain by ensuring the survival of the population and their offspring as well as giving birth to new populations. When searching and locating food sources, ants use pheromons for communication. They show warrior strategies for fighting enemies. And they always adapt to their environment in terms of food, war, weather conditions. Ants might even adapt distribution of their roles such as creating more warriors when necessary. The whole population appears as a kind of smart creature.
A human might also be considered as a whole consisting of smaller agents (cells) and this is how evolution actually developed complex life forms.
And if you think about it, the Web itself is just an emergent system.
When we are going to build such an emergent system, we need to consider all these aspects defined above such as roles, hierarchies, communication styles, goals, controls, environment, adaptation, cooperation strategies.
One promising way to implement such systems are Actor-based approaches.
If we had a toolkit for emergent system that allows to configure the different variation points, we could play around with the concept. Akka is one of the excellent frameworks that could serve as a base for such a toolkit.
So, eventually emergent systems are developed using emergent design approaches. Until then, there is a large journey ahead of us.