swarm intelligence
In plain wordsThe teamwork that appears when crowds of simple creatures or machines, such as ants, bees or small robots, each respond only to what is nearby, with nobody in charge, yet together solve problems.
Adaptive behavior shown by a decentralized collective as a whole rather than by any member — an ant colony converging on the shortest route to food, a flock turning in unison — together with the algorithms and robot-control methods modeled on it. Each agent senses only its surroundings and follows a few fixed rules, and nothing holds a global plan; colony-level results such as foraging trails, nest construction and division of labor are produced by positive and negative feedback, randomness and stigmergy, indirect coordination through traces left in the environment such as pheromones. Algorithmic examples include ant colony optimizationant colony optimization, n.: A method for finding good routes and schedules inspired by how ants find short paths to food: simulated ants leave 'scent' on good paths, which attracts other ants, so the best routes gradually stand out., particle swarm optimizationparticle swarm optimization, n.: An optimization method inspired by flocking birds: candidate solutions 'fly' through the space of possibilities, each pulled toward the best spot it has found and the best spot its neighbors have found. and artificial bee colony algorithms; physical applications include swarm roboticsswarm robotics, n.: Coordinating large groups of simple robots that follow local rules and talk only to their neighbors, so useful group behavior emerges without a central controller, as in ant colonies or bird flocks. (drone light shows, by contrast, are usually choreographed centrally rather than self-organized). Such systems are valued for robustness, scalability and flexibility, but their emergent behavior can be hard to predict or verify.
Origin
Coined by Gerardo Beni and Jing Wang in 1989 in work on cellular robotic systems presented at a NATO workshop in Italy. Craig Reynolds's 'boids' flocking simulation (1987) and studies of social insects were key influences, and Eric Bonabeau, Marco Dorigo and Guy Theraulaz's 1999 book defined the field.
Usage note
Distinct from agent swarmsagent swarm, n.: A large group of AI agents working at the same time on parts of a problem, usually with little central control — a name loosely borrowed from swarms of insects. of language-model agents, which borrow the word but typically use a few highly capable agents with explicit coordination, and from the 'wisdom of crowds' in human judgment.
Related
- ant colony optimizationant colony optimization, n.: A method for finding good routes and schedules inspired by how ants find short paths to food: simulated ants leave 'scent' on good paths, which attracts other ants, so the best routes gradually stand out.
- particle swarm optimizationparticle swarm optimization, n.: An optimization method inspired by flocking birds: candidate solutions 'fly' through the space of possibilities, each pulled toward the best spot it has found and the best spot its neighbors have found.
- swarm roboticsswarm robotics, n.: Coordinating large groups of simple robots that follow local rules and talk only to their neighbors, so useful group behavior emerges without a central controller, as in ant colonies or bird flocks.
- evolutionary computationevolutionary computation, n.: Problem-solving by simulated evolution, much as breeders improve crops: keep many candidate answers, let the better ones produce slightly altered offspring, drop the worse, and repeat for many rounds.
- agent swarmagent swarm, n.: A large group of AI agents working at the same time on parts of a problem, usually with little central control — a name loosely borrowed from swarms of insects.
- metaheuristicmetaheuristic, n.: A general-purpose strategy for finding good answers to hard problems, such as imitating evolution or cooling metal, that can be adapted to many different problems instead of being designed for just one.
Sources
- Beni, G. & Wang, J. (1993). Swarm Intelligence in Cellular Robotic Systems. In Robots and Biological Systems: Towards a New Bionics? NATO ASI Series F 102. Springer. (Workshop held 1989.)
- Bonabeau, E., Dorigo, M. & Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press.
Mentioned in
evolutionary computationevolutionary computation, n.: Problem-solving by simulated evolution, much as breeders improve crops: keep many candidate answers, let the better ones produce slightly altered offspring, drop the worse, and repeat for many rounds., agent swarmagent swarm, n.: A large group of AI agents working at the same time on parts of a problem, usually with little central control — a name loosely borrowed from swarms of insects., ant colony optimizationant colony optimization, n.: A method for finding good routes and schedules inspired by how ants find short paths to food: simulated ants leave 'scent' on good paths, which attracts other ants, so the best routes gradually stand out., artificial lifeartificial life, n.: The study of life by building lifelike systems — in computer simulations, robots or chemistry — to learn how living things organize themselves, reproduce and evolve, and what other kinds of life could exist., computational intelligencecomputational intelligence, n.: A family of AI methods inspired by nature, such as neural networks, fuzzy logic and evolutionary algorithms, that learn or adapt from numbers rather than following explicit logical rules., metaheuristicmetaheuristic, n.: A general-purpose strategy for finding good answers to hard problems, such as imitating evolution or cooling metal, that can be adapted to many different problems instead of being designed for just one., particle swarm optimizationparticle swarm optimization, n.: An optimization method inspired by flocking birds: candidate solutions 'fly' through the space of possibilities, each pulled toward the best spot it has found and the best spot its neighbors have found., soft computingsoft computing, n.: A group of computing methods, including fuzzy logic, neural networks and evolutionary algorithms, that accept imprecise, approximate answers in exchange for being practical on messy real-world problems., swarm roboticsswarm robotics, n.: Coordinating large groups of simple robots that follow local rules and talk only to their neighbors, so useful group behavior emerges without a central controller, as in ant colonies or bird flocks.