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Particle Swarm Optimization (PSO)

Metaheuristic optimization inspired by the social behavior of bird flocks or fish schools, where 'particles' explore the search space by adjusting their trajectory based on their own experiences and those of their neighbors.

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Ant Colony Algorithm (ACA)

Probabilistic combinatorial optimization method based on the food foraging behavior of ants, using artificial pheromone trails to find optimal paths in a graph.

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Collective Behavior

Set of actions and patterns resulting from simultaneous interactions of multiple agents within a group, producing group dynamics greater than the sum of individual behaviors.

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Swarm Robotics Intelligence

Application of swarm principles to physical robots, enabling them to accomplish complex tasks collaboratively and robustly, without central supervision, such as in exploration or mapping.

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Artificial Bee Colony Algorithm (ABC)

Optimization metaheuristic inspired by the foraging behavior of bees, where 'employed bees', 'onlookers', and 'scouts' explore and exploit solutions to find a global optimum.

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Sensor Swarm

Distributed network of numerous simple and autonomous sensors that collaborate to monitor an environment, using swarm principles for self-organization, data collection, and transmission.

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Artificial Cicada Algorithm

Optimization metaheuristic inspired by the mating behavior of cicadas, where agents emit signals to attract partners, modeling an exploration and exploitation mechanism.

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Scalability

Ability of a swarm system to maintain its performance and self-organization capacity when the number of agents increases significantly, without requiring complex restructuring.

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