Cultural Algorithms employ a basic set of knowledge sources, each related to knowledge observed in various social species. These knowledge sources are then combined to direct the decisions of the individual agents in solving optimization problems. Here we develop an algorithm based upon an analogy to the marginal value theorem in foraging theory to guide the integration of these different knowledge sources to direct the agent population. Application to real-valued function optimization and an optimization problem in engineering design are used to illustrate the principles.
Citation:
Robert G. Reynolds, Bin Peng, "Knowledge Integration On-The-Fly in Swarm Intelligent Systems," ictai, pp.197-210, 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06), 2006