Hello Mohammad, thanks for your good and intresting question.

The idea behind swarm intelligence is to learn from what happens in nature. "It's why fish form schools and birds form flocks and bees form swarms," said Rosenberg. "In a nutshell, it's allowing the group to make better decisions than individuals could make alone." This type of swarm intelligence, it should be noted, is not quite the same as another kind called "flocking," which applies to robotics. "Flocking" is a way that groups can efficiently navigate through environments, relying on each other for help.

This framework helped identify — using similar system attributes — where collective intelligence might exist.

Multi-agent system.

No central operator.

No centralized communication.

Unified utility function.

Agents run reinforcement learning algorithms for validation.

Swarm intelligence is the self-organization of systems for collective decentralized behavior. Swarm intelligence enables groups to converge and create an independent organism that can do things that individuals can’t do on their own. It is the response of the system or organism to various stimuli or inputs, whether internal or external, conscious or subconscious, overt or covert, and voluntary or involuntary.

The difference is the Knowledge of the end goal. swarm Computing is coincidencal and can withstand risks. The swarm intelligence in contrast is made up by organisms with a sense of survival and has the ability to communicate and where each agent has an agenda. Fish detect ripples in the water. Birds use motion detected through the flock. Ants leverage chemical traces

About swarm intelligence

While the bees are engaging in "real-time negotiation," humans often have a different, less accurate approach to making predictions. Typically, humans use polls and votes, which Rosenberg calls "primitive." They're often wrong, he said, because they're polarizing. "Instead of finding common ground, they force us to entrench in predictions and make it harder for us to find the best answer for the group."

About computing intelligence

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." Computing is any goal-oriented activity requiring, benefiting from, or creating a mathematical sequence of steps known as an algorithm — e.g. through computers. Technology-based distributed systems are collections of independent computers that appear to work as a unified, coherent system. This same effect is found in swarms. The common element is that control is distributed across individuals or entities and communication isn’t localized.

artificial swarm intelligence is computational intelligence. Note the word artificial

“We focus on a unique form of artificial intelligence called artificial swarm intelligence,” UNU’s creator Louis Rosenberg tells Newsweek. “Ninety-nine percent of AI currently being developed is about replacing and ultimately exceeding human intelligence. Ours is different. It’s about amplifying human intelligence.”

https://www.cio.com/article/3192068/artificial-intelligence/why-swarm-intelligence-enhances-business-and-bitcoin.html

http://www.newsweek.com/swarm-intelligence-ai-algorithm-predicts-future-418707

https://www.techrepublic.com/article/how-artificial-swarm-intelligence-uses-people-to-make-better-predictions-than-experts/

https://atos.net/en/blog/swarm-computing-goes-around-comes-around

Elizabeth A. Minton, Lynn R. Khale (2014). Belief Systems, Religion, and Behavioral Economics. New York: Business Expert Press LLC. ISBN 978-1-60649-704-3.

Swarm Intelligence (SI) is a kind of artificial intelligence that aims to simulate the behavior of swarms or social insects. Swarm refers to any loosely structured collection of interacting agents. Technically swarms are regarded as decentralized self-organized systems. Swarm intelligence has a multidisciplinary character its study provides insights that can help humans manage complex systems. There is no clear definition for swarm intelligence. Emergent behaviour, self-organized behaviour and collective intelligence are the related terms. Surprisingly swarm intelligence system has the ability to act in a coordinated way without any coordinator or external controller.

Swarm Intelligence of Ants

Collective intelligence is the key. A single ant, for example, is not that smart but a colony of ants is. As colonies, ants respond quickly and effectively to their environment. They find shorted path to the best food source, allocate workers to different tasks, and defend their territory from enemies. Ant colonies make these possible by countless interactions between individual ants. Each ant follows a simple rule of thumb. Each ant acts only on local information. A system that exhibits this behavior is said to be self-organizing. And the intelligence the ants exhibit collectively is called swarm intelligence.

Marco Dorigo, at the Université Libre in Brussels, used swarm intelligence in 1991 to create mathematical procedures for solving complex problems, such as routing trucks, scheduling airlines, or guiding military robots.

Swarm intelligence is “the emergent collective intelligence of groups of simple agents” (Bonabeau et al, 1999), which is typically captured by understanding and computationally reproducing natural phenomena. An important principle of swarm intelligence is stigmergy that assumes that work can be continued by any individual in the swarm, different configurations can be made according to the environmental state, and modification of performance is the result of indirect agent interaction.

With the objective of achieving optimized and robust system performance, swarm computing creates distributed systems of interacting autonomus agents, applies self-organized and decentralized control and cooperation, divides labour and allocates tasks in an undistinct and distributed manner, and implement indirect interactions. Some forms of swarm computing also try to reduce some drawbacks of traditional computing such as the need for algoritmically well-defined procedure, intolerance to incompleteness and uncertainty, sequential computation regime, and discrete computational cycles.