Agent-Based GLOs/SLOs for STEM

This chapter deals with the problem on how to enforce additionally the smart capabilities of the generative learning objects (GLOs) by connecting them with agent-based technology. We consider two aspects of this wide problem only. Firstly, we investigate similarities and differences among meta-programming-based GLOs and software agents. The result is that one can consider a GLO as a weak software agent without the autonomy in decision-making while selecting parameter values. Secondly, we introduce the technological agent enabling to replace the human’s actions in selecting technological parameter values by the agent. The provided experiment showed that using this agent it is possible to achieve a higher robot’s accuracy. The main contribution of this chapter is the agent-based architecture of the system and its partial implementation, enabling to solve the prescribed tasks more efficiently, i.e. with a less user’s intervention and a higher robot’s accuracy.

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