Recently, the general idea of "shaping" used by ethology, behavior analysis or animal training is a remarkable method. "Shaping" is a general idea that the learner is given a reinforcement signal step by step gradually and inductively forward the behavior from easy tasks to complicated tasks. In this paper, we propose a shaping reinforcement learning method took in a general idea of Shaping to the reinforcement learning that can acquire a desired behavior by the repeated search autonomously. Three different shaping reinforcement learning methods used Q-Learning, Profit Sharing, and Actor-Critic to check the efficiency of the Shaping were proposed at first. Furthermore, we proposed the Differential Reinforcement-type Shaping Q-Learning (DR-SQL) applied a general idea of "differential reinforcement" to reinforce a special behavior step by step such as real animal training, and confirmed the effectiveness of these methods by the simulation experiment of grid search problem.
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