Swarm intelligence refers to the collective intelligence of a group of species. Natural scientists have been studying the behavior of social animals and insects to understand their ability to solve complex problems efficiently. Though these insects or animals are not so sophisticated individually, they are remarkable as a group or swarm when interacting with each other or their environment. None of the individuals is giving orders and yet each of the individuals in the swarm seem to know precisely what needs to be done.
The key to this lies in the fact that each individual follows a small set of rules related to its local environment. These rules help these social insects or animals solve complex problems as a group, a feat they cannot achieve individually. Let’s look at a classic example to help demonstrate this principle.
Ants go out in search of food, exploring their surroundings in no fixed manner. And as they scout the near-by areas, they leave behind pheromones. Once an ant finds food, it follows it pheromone trail back to its nest. As it goes back and forth to collect food, the pheromone trail gets stronger, while the rest of the ants follow this trail to collect food and leave it back at the nest.
Though other ants also find paths to the food source, they eventually switch to following the strongest trail. This way, all the ants end up going in a straight line that is also the shortest path to the food source. As ants stumble upon other trails, the shortest path gets reinforced while the longer ones slowly disappear.
A typical swarm intelligence system has a few common characteristics.
It has been noted that in social animals there are no leaders. Every individual in the group works for the benefit and welfare of the group. With no leaders, there is no need for permissions. And each individual works based on the information received from the closest individual in proximity or collectively.
It isn’t a surprise then that these individuals do have knowledge of the bigger plan. For example, there are two kinds of information are gets shared among bees. They are information about food and threat. When bees find a good source of nectar, they perform a waggle dance and signal to others the newly found source of nectar. Similarly, when looking for a new place to relocate the hive, the bees perform a different waggle dance to signal the newfound place to the other bees. Even information of threat is communicated in a similar way as a group.
As mentioned earlier, since there are no leaders, individuals of a social group do not require to take permissions or orders from anyone. This means, there is no hierarchy in the group. Every individual does what they are required to do in an organized manner. There is a clear understanding of what each individual is required to do within each context.
One of the key reasons for the absence of hierarchy in such social groups is the need for speed and agility. And this is crucial for the survival of the group.
These characteristics enable us to design artificial swarm intelligence systems that are error-free and scalable.
These systems are capable of maintaining their core functions though the size is increased. The interactions between the individual parts of the system do not have to be redefined. As a rule, since the interactions of the individuals are limited to that of their neighboring individuals, the overall number of interactions does not grow even if the size of the swarm increases. What this essentially means for the artificial swarm system is that the performance of the system can be increased without having to reprogram the entire system.
Since individuals in a swarm are required to perform different actions in different places, this kind of intelligence helps us build systems where parallel actions can be run. This feature in an artificial system enables flexibility and self-organizing. This way different aspects of a complex task can be taken care of simultaneously.
Being error-free is an inherent aspect of swarm intelligence. This is attributed to the decentralizing nature of control that these groups exhibit. Since individuals in a swarm can be interchanged swiftly and since there is no leader or hierarchy, a flawed individual can be quickly replaced by another individual. This way the overall functioning of the swarm remains intact and unaffected.
By studying the behavior of social insects and animals, several companies have implemented these patterns to derive optimal results from their business. Some of the noteworthy mentions of companies that turned to artificial swarm intelligence include Southwest Airlines, Unilever, McGraw-Hill, Capital One etc. Such companies have developed effective ways to organize and schedule factory equipment, divide tasks efficiently among their employees and workers, organize people, and even come up with strategies for their business development.
Some of the ways in which you can use artificial swarm intelligence include
Artificial swarm intelligence platform or software has been successfully used across industries. The possibilities are limitless, and its future implementation is only limited by our own imagination. Brainalyzed is an artificial swarm intelligence software that is enabling companies in the Finance industry to build better and risk-free businesses. If you’d like to talk about what we’re building, let us know in the comments below.
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