Online Knowledge Acquisition and General Problem Solving in a Real World by Humanoid Robots

Abstract

In this paper, the authors propose a three-layer architecture using an existing planner, which is designed to build a general problemsolving system in a real world. A robot, which has implemented the proposed method, forms the concepts of objects using the Self-Organizing Incremental Neural Network, and then acquires knowledge, online and incrementally, through interaction with the environment or with humans. In addition, it can solve general-purpose problems in a real world by actively working with the various acquired knowledge using the General Problem Solver. In the experiment, the authors show that the proposed method is effective for solving general-purpose problems in a real world using a humanoid robot.