End-To-End Automated Self-Learning Robotic Systems

Recently, there has been a lot of interest in robotic process automation from both business and academics. Robotic process automation, also known as RPA, is a set of technologies and methods that entrepreneurs may use to automate manual operations that are repetitive. RPA has undeniable inherent benefits; automation, for example, lowers expenses and mistakes and improves the overall efficiency of corporate operations. However, with the present generation of RPA technology, the jobs that need to be automated have to be found, elicited, and coded by humans. We can monitor user activity on the front end in the meantime thanks to a variety of methods at our disposal. Therefore, based on collected user behaviour, we provide in this study a unique end-to-end approach that enables fully automated, algorithmic development of RPA rules. Furthermore, we provide a proof-of-concept prototype for our suggested methodology that is accessible to the general public.