Swarm intelligence metaheuristics are a part of a large group of nature-inspired optimization algorithms. In this paper, we introduce a new PSO-inspired algorithm, that incorporates the positive experiences of the swarm to learn the geometry of the search space,thus obtaining the ability to consistently reach global optimum. During the comparative analysis, it has been found to consistently outperform the other swarm-intelligence based algorithms on the family of benchmarks.