Particle Swarm Optimization (PSO) is a computational method used for solving optimization problems. It is inspired by the social behavior of birds and fish, where individuals in a group communicate and share information to find food or navigate. In PSO, potential solutions, called "particles," move through a solution space, adjusting their positions based on their own experiences and those of their neighbors. Each particle evaluates its position using a fitness function, which measures how good the solution is. Over time, particles converge towards the best solutions found, effectively exploring the search space and improving their performance. PSO is widely used in various fields, including engineering and artificial intelligence.