Social Development

Work on leveraging optimization with mixed individual and social learning appears on Applied Soft Computing


We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Cooperative Group Optimization (CGO), to show the leveraged optimization with a mixed individual and social learning. In CGO-AS, each ant (agent) is added with an individual memory, and is implemented with a novel search strategy to use individual and social cues in a controlled proportion. The presented CGO-AS is therefore especially useful in exposing the power of the mixed individual and social learning for improving optimization. The results prove that a cooperative ant group using both individual and social learning obtains a better performance than the systems solely using either individual or social learning.