Swarm Optimization: Goodbye Gradients

These combinations of real-time biological systems can blend knowledge, exploration, and exploitation to unify intelligence and solve problems more efficiently. These simple agents interact locally, within their environment, and new behaviors emerge from the group as a whole. In the world of evolutionary alogirthms one such inspired method is particle swarm optimization (PSO). It is a swarm intelligence based computational technique that can be used to find an approximate solution to a problem by iteratively trying to search candidate solutions (called particles) with regard to a given measure of quality around a global optimum. The movements of the particles are guided by their own best known position in the search-space as well as the entire swarm's best known position.