We have already proposed Fuzzy Interpolation-Based Q-Learning where fuzzy rules are used to represent Q-function (action utility function), in order to enable us to treat continuous-valued states and actions. In. this paper, we will introduce the idea of Profit Sharing Plan (PSP) used in Classifier Systems into the Fuzzy Interpolation-Based Q-Learning in order to accelerate the speed of learning and will discuss its effectiveness through applications to control problems such as cart-pole balancing problems.