An Agent Control Method Based on Variable Neighborhoods

In this paper, we propose a model that an agent selects actions based on variable neighborhoods. We formulate relationships among variable neighborhoods, the agent's observations, and the agent's behaviors in a framework of rough set theory and topological spaces. The main task is to explore a method by which we can select sizes of neighborhoods under given contexts. We also show simulation results of the proposed method.