1. An object recognition system incorporating swarming domain classifiers, comprising: at least one cognitive map having a one-to-one relationship with an input image domain, the cognitive map being capable of recording information that software agents utilize to focus a cooperative swarm's attention on regions in the domain most likely to contain objects of interest; a plurality of software agents configured to operate as a cooperative swarm to classify an object in the domain, where each agent is a complete classifier and is assigned an initial velocity vector to explore a solution space for object solutions, where each agent is configured to perform at least one iteration as influenced by the recorded information of the cognitive map, the iteration being a search in the solution space for a potential solution optima where each agent keeps track of its coordinates in multi-dimensional space that are associated with an observed best solution (pbest) that the agent has identified, and a global best solution (gbest), where the gbest is used to store the best location among all agents, with each velocity vector thereafter changing towards pbest and gbest, allowing the cooperative swarm to concentrate on the vicinity of the object and classify the object when a classification level exceeds a preset threshold.