Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
Generally, it is known that the engineering application simulated from the learning mechanism of animals is useful. Above all, the general idea of "Shaping" used by ethology, behavior analysis or animal training is a remarkable method recently. "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.
