chapter seven – The Particle Swarm

Publisher Summary This chapter introduces the particle swarm in its binary and real-numbered forms. The particle swarm algorithm is discussed in terms of social and cognitive behavior, though it is widely used as a problem solving method in engineering and computer science. The chapter presents more commonly used version, which operates in a space of real numbers. The process of cultural adaptation comprises a high-level component, seen in the formation of patterns across individuals and the ability to solve problems, a low-level component, the actual and probably universal behaviors of individuals, which can be summarized in terms of three principles: evaluation, comparison, and imitation. These three principles may be combined, even in simplified social beings in computer programs, enabling them to adapt to complex environmental challenges, solving extremely hard problems. The progression of ideas has been from a purely qualitative social optimization algorithm—the Adaptive Culture Model—to a model that can be interpreted as qualitative or quantitative—the binary particle swarm. The kind of decision processes instantiated in both the binary and real-valued particle swarm algorithms exemplify a tendency that is widely regarded as a flaw or error when seen in human cognition.