Research on a Multi-Objective Genetic Algorithm for Rational Agent Learning Model
As a software component which is capable of learning in an autonomous way, software agent should have the capability of learning in a dynamic environment. Genetic Algorithm has a wide perspective in the machine learning because of its unique characteristic (e.g. dynamic adaptability, self-organization, global convergence and robustness). But when applying GA to agent’s dynamic learning model, it encounters a series of problem. In this paper, a Modifided Multi-Objective Genetic Algorithm(MMOGA) will be introduced to solve these problems. Finally, an Agent’s Dynamic learning model based on a MMOGA which has the flexible dynamic learning capability, better global convergence and performance, will be introduced.
M. Li et al., "Research on a Multi-Objective Genetic Algorithm for Rational Agent Learning Model", Applied Mechanics and Materials, Vols. 58-60, pp. 1232-1239, 2011