Swarm intelligence

Swarm intelligence is a way that groups of simple individuals work together to do smart things without anyone telling them what to do. This idea was first used in 1989 by scientists Jing Wang and Gerardo Beni when they studied groups of robots.

A flock of starlings reacting to a predator

In nature, we can see swarm intelligence in many places. Ants work together to find food, bees organize their hives, birds fly in groups called flocks, and fish swim together in schools. Even tiny living things like bacteria show this kind of teamwork. Each individual follows just a few simple rules, but together they create behaviors that are much smarter than any one of them could do alone.

Scientists use the idea of swarm intelligence to make computer programs and robots that can solve problems by working together. This is called swarm robotics. It can also help us understand how living things work and even help make new kinds of living organisms that can work as a team.

Models of swarm behavior

Boids (Reynolds 1987)

Main article: Boids

Boids is a computer program made in 1986 by Craig Reynolds. It pretends to show how birds fly together in a group. Boids acts like real birds because each pretend bird follows just a few simple rules. These rules are to stay away from bumping into other birds, to point in the same way as birds nearby, and to move toward where the group is going. More rules can be added, like avoiding things or moving toward a goal.

Self-propelled particles (Vicsek et al. 1995)

Main article: Self-propelled particles

Self-propelled particles is a way to pretend that small things move in a group. It was made in 1995 by Vicsek and others, based on the Boids program. In this model, each tiny thing moves at the same speed but changes direction by looking at the direction of others close by. This helps scientists understand how real groups of animals, like birds or fish, act together.

Social potential fields (Reif et al. 1999)

Main article: Social potential fields

Social Potential Fields is a way to make many robots move together. It was made in 1999 by John H. Reif and Hongyan Wang. This method pretends that robots feel pushes and pulls on each other, like tiny forces. These forces can make robots move away from each other when close, or pull together when far apart. By using these forces, robots can do jobs like staying in a group, watching an area, or moving something together. This method works even if the robots make small mistakes, which makes it very useful.

Metaheuristics

Evolutionary algorithms, particle swarm optimization, differential evolution, ant colony optimization and their variants are important in the study of nature-inspired problem-solving methods. These methods help find good solutions to difficult problems by mimicking natural processes.

Metaheuristics are special ways to solve problems that don’t always guarantee the perfect answer but often find very good solutions. One example is Ant-inspired Monte Carlo algorithm for Minimum Feedback Arc Set, which combines ideas from ant behavior with chance-based methods to improve results.

Ant colony optimization (Dorigo 1992)

Main article: Ant colony optimization

Ant colony optimization (ACO) is inspired by how real ants find food. In this method, computer programs act like ants to find the best paths or solutions. Real ants leave smells to guide each other, and in ACO, the programs remember where they’ve been and how good those places are, helping find better solutions over time.

Particle swarm optimization (Kennedy, Eberhart & Shi 1995)

Main article: Particle swarm optimization

Particle swarm optimization (PSO) is a way to find the best solution by treating each possible answer as a point moving in space. These points, or particles, move around and share information. Over time, they head towards the best solutions found by others in their group.

Artificial Swarm Intelligence (2015)

Artificial Swarm Intelligence (ASI) is a way to boost the smart thinking of groups of people by using rules inspired by how swarms in nature work. This technology links people together in real time to solve problems together, like making better financial predictions, improving medical diagnoses, and helping organizations forecast events such as food shortages.

Applications

Swarm Intelligence-based techniques can be used in many useful ways. The U.S. military is looking into swarm methods to control unmanned vehicles. The European Space Agency is thinking about using a group of satellites for building and measuring things in space. NASA is exploring swarm technology for mapping planets. Swarm intelligence is also being used in Internet of Things (IoT) systems, helping to manage complex tasks through simple, self-organizing rules. It is applied in data mining and grouping information.

Swarm intelligence is useful in many everyday areas. It helps with planning routes, scheduling tasks, and sharing resources efficiently. In robotics, it helps many robots work together for tasks like searching and rescuing people, organizing warehouses, and watching the environment. It is also used in networks to move data quickly and efficiently.

Additionally, swarm intelligence is important in traffic systems, helping to control traffic lights and reduce congestion in cities. In healthcare, it helps with finding new medicines and studying genes. It is also used in games and simulations to create realistic group movements, like flocks of birds or crowds of people.

Ant-based routing

Swarm intelligence is used in telecommunication networks through ant-based routing. This method was developed in the mid-1990s and uses simple control messages, called "ants," to find the best paths for data. This helps in deciding where to place communication towers for wireless networks. Airlines, like Southwest Airlines, use swarm ideas to assign planes to gates efficiently, helping pilots find the best gates quickly and avoid delays.

Crowd simulation

Artists use swarm technology to create realistic crowd scenes in movies. For example, The Lord of the Rings film trilogy used similar technology for battle scenes. Swarm technology is also used to simulate groups of fish and birds in films. Airlines have used swarm theory to study how passengers board planes.

Human swarming

People can also work together in groups, called "human swarms," using real-time control systems. This lets groups of people work together online to solve problems better than individuals. Studies show that groups of doctors using these swarming methods can diagnose medical conditions more accurately than traditional methods.

Swarm grammars

Swarm grammars are groups of rules that can describe complex patterns, like those found in art and architecture. These rules work together like a swarm to create and suggest learning methods.

Swarmic art

Artists have used swarm intelligence to create new kinds of art. By mimicking how ants forage and birds flock, they can produce sketches and paintings that change each time. These systems explore creativity through the balance of freedom and rules in swarm behavior.

Michael Theodore and Nikolaus Correll use swarm intelligence in art installations to make engineered systems look more lifelike.

Notable researchers

Here are some important people who have studied swarm intelligence: