Interactive intelligent agents with creative minds: Experiments with mobile robots in cooperating tasks by using machine learning

Abstract

In this paper, we present an intelligent system where agents can co-ordinate creative tasks through machine learning and cooperation. For machine learning, we used commonly used pattern recognition algorithm - Principal Component Analysis (PCA). Based on recognition, we plan a task that is performed by multiple intelligent agents. In our case, task is to draw a pattern or perform a creative art by agents. The task action is divided into three phases: obtaining a design, composing a mathematical model and and performing the task by agents. In case of agents co-ordination, various feedback techniques using wireless sensors and on-board sensors are used. As for proof of concept (POC), a flower pattern is detected, which is painted on a canvas by using mobile robots. Also, person's identity and mood is detected and then a creative art is performed by mobile robots to improve the mood.