Active learning from cross perceptual aliasing caused by direct teaching

Abstract

Proposes an active learning method by which the learner has capabilities of self-learning and understanding the instructions by coping with cross perceptual aliasing problem caused by the state space difference between the learner and the teacher. The learner asks the teacher to give an appropriate instruction when necessary to reduce the instruction frequency. Further, the learner finds taught data inconsistent with learner's state space caused by cross perceptual aliasing, and modifies its state space based on the clustering method C4.5 so that it can successfully achieve the goal by reinforcement learning. The method is applied to the domain of RoboCup, where a learning robot attempts to approach and shoot a ball into the goal with the help of instructions given by teacher on request. The experimental results are shown and a discussion is given.