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Examples of swarm intelligence in natural systems include ant colonies, bee colonies, bird flocking, hawks hunting, animal herding, bacterial growth, fish schooling and microbial intelligence. The application of swarm principles to robots is called swarm robotics while swarm intelligence refers to the more general set of algorithms.
Swarm Intelligence : From Natural to Artificial Systems with Eric Bonabeau and Guy Theraulaz, Oxford University Press, 1999 (ISBN 0-19-513159-2). Robot Shaping with Marco Colombetti, MIT Press, 1998 (ISBN 0-262-04164-2). Ant algorithms for discrete optimization with Gianni Di Caro and Luca Maria Gambardella, Artificial Life, Vol. 5, N. 2, 1999.
This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, [ 6 ] [ 7 ] the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path ...
Gerardo Beni (born Florence, Italy 21 February 1946) is a professor of electrical engineering at University of California, Riverside who, with Jing Wang, is known as the originator of the term swarm intelligence [1] [2] in the context of cellular robotics and the concept of electrowetting, [3] with Susan Hackwood.
The design of swarm robotics systems is guided by swarm intelligence principles, which promote fault tolerance, scalability, and flexibility. [1] Unlike distributed robotic systems in general, swarm robotics emphasizes a large number of robots. While various formulations of swarm intelligence principles exist, one widely recognized set includes:
Bat algorithm is a swarm-intelligence-based algorithm, inspired by the echolocation behavior of microbats. BA automatically balances exploration (long-range jumps around the global search space to avoid getting stuck around one local maximum) with exploitation (searching in more detail around known good solutions to find local maxima) by ...
ABC belongs to the group of swarm intelligence algorithms and was proposed by Karaboga in 2005. A set of honey bees, called swarm, can successfully accomplish tasks through social cooperation. In the ABC algorithm, there are three types of bees: employed bees, onlooker bees, and scout bees.
The Fireworks Algorithm (FWA) is a swarm intelligence algorithm that explores a very large solution space by choosing a set of random points confined by some distance metric in the hopes that one or more of them will yield promising results, allowing for a more concentrated search nearby.