There is an interesting analysis of collective phenomenon (feedback loop type) that lead to emergence of properties at the following link http://ea2000.unipv.it/Sistemi_combinatori/genindex.htm

Hi, if by Swarm Intelligence we mean a fully-decentralised approach in which each individual has the (more or less) same, simple behaviour, then we can achieve a high expressiveness in the way we define, compose, and reuse "components" of collective adaptive behaviour, there including decision making. Please, check this work for a starting point:

https://www.researchgate.net/publication/282270919_Aggregate_Programming_for_the_Internet_of_Things?ev=prf_pub

Article Aggregate Programming for the Internet of Things

 I do agree with the fact that a form of intelligence may emerge from the natural tendency of  single units to imitate the behavior of their  surrounding units. I would like to stress the main properties that are necessary for the swarm intelligence to emerge.

The strength of imitation must be strong enough as to generate a phase transition from the conditions where the single units are virtually independent the ones from the others to a condition where a global behavior emerges. However, an excessive effort to imitate the behavior of the nearest neighbors may produce a super-critical regime and this is not good for the efficiency of the system and it corresponds to a lack of intelligence. To explain this important fact, let me mention the  swarm model where each bird selects the flying direction of its nearest neighbors. If the imitation strength is very strong the swarm flies in a given direction as a single organism. Let us imagine now that a predator comes and that the majority of the birds imbedded in the swarm do not see it. The lookout birds do, but if heir number is very small they do not succeed in forcing the swarm to change direction. 

If the swarm is at criticality, namely at the border between the erratic behavior of many independent units and the global flight in a given direction, frequent organization collapses occur. I define "free will" the occurrence of an organization collapse. When the free will condition is realized the swarm selects the new flying direction randomly,as a result of a nucleation process around a small fluctuation from the condition of vanishing velocity. This condition of free will is important because if we identify the lookout birds with consciousness, we see that a properly chosen flying direction can be adopted by the swarm. The action that the lookout birds have to exert on the swarm has to be larger that the very weak fluctuations that make the swarm change direction in a random way.  In other words, even if the number of lookout birds is very small, at criticality, like the committed minorities of human societies, they can force the swarm to change flying direction. 

Furthermore the action of the lookout birds (the consciousness) is facilitated by the fact  that criticality generates long-range correlation making it possible for the blind birds to perceive the change of direction of the lookout birds. In spite of this "instantaneous" communication, it take some time for the swarm to change direction because it requires the occurrence of organization collapses. The lack of organization collapses is equivalent to the lack of a free will.

All these ideas are illustrated in the following two papers:

F. Vanni, M. Lukovic, P. Grigolini, ``Criticality and Transmission of Information in a Swarm of Cooperative Units”,  Phys. Rev. Lett. 107, 078103 (2011).

 M. Lukovic, F. Vanni, A. Svenkeson, P. Grigolini, “Transmission of information at criticality”, Physica A, 416, 430-438 (2014). 

Indeed, collective of non-humans can make smart collective decisions. However, individuals are not super-rational (like Homo economicus) but may behave using very primitive algorithm, like sensitivity to population density or some physical variable, like temperature.

In order for humans to learn something from this swarm intelligence, we need to focus on such applications where individual rationality is not needed for a smart collective decision, but rather some sensitivity to jointly observable parameter. For example, when you see tsunami wave - just run to mountains.

In this context is possible talking about "collective decision making"? I think, it's not possible. It's "collective behavior" not "collective decision making" as like as . It's not collective decision system in an ontological point of view.

Jesus, you are right: this is more like collective behavior. We cannot expect ants to be rational but we observe patterns of their social activity.

I think that SI may also be an algorithm for self-organizing behavior of robots in a battle when communication is limited.

In economic systems we can also observe self-organizing patterns like markets where agents just react on signals (like price). There are models of stock market based on bounded rational behavior.

Dear Yuri:

You are right but collective behavior patterns (as phenomenon, as algorithm) are not 'before' behavior (cause) but in reverse order. In robots, also, there is not behavior and there is nor rational self-organization, I think, because they are not rational and free agents. Robots are deterministic agents.

In economic systems agents are rational but not all are really-free agents because many systems are coercive environments. So, coercive decision systems and decision making is not explained by rational choice theory.  So economic systems may being considered rational systems but not self-organized ones, I think, because freedom is the main prerequisite for self-organized behavior in a really-free (but in context) environment. There is not any possible a 'total-free' environment for all agents, but only a bounded-free environment.

Regards,

Dear @Sidartha, I find this article is very relevant for your issue.

How 'artificial swarm intelligence' uses people to make better predictions than experts?

"Dr. Louis Rosenberg, CEO of Unanimous AI, is building a software platform, UNU, that assembles groups to make collective decisions. "What's different about this is that it fundamentally keeps people in there," he said. "We're focused on using software to amplify human intelligence."...

UNU is an online platform where anyone can log in and answer questions as a swarm. "People benefit when they form a real-time system the way bees, fish, and birds do, as opposed to people just casting a single vote the way people do," said Rosenberg..."

http://www.techrepublic.com/article/how-artificial-swarm-intelligence-uses-people-to-make-better-predictions-than-experts/?tag=nl.e101&s_cid=e101&ttag=e101&ftag=TRE684d531