Robot-Oriented Generative Learning Objects: An Agent-Based Vision

The paper presents a juxtaposing of the robot-oriented generative objects (GLOs) with software (SW) agents and identifies the capabilities to introduce more intelligence to the educational environment based on those GLOs. The main contribution of the paper is the agent-based architecture of the system and its partial implementation, enabling to solve the prescribed tasks more efficiently (with a less user’s intervention and a higher robot’s accuracy). Also the case study and some experimental results are described.