Design and Development of Chatbot Based on Reinforcement Learning

Systems consigned with machine learning (ML) as well as artificial intelligence (AI) can think, learn, and remember. Thus today, AI/ML are key technologies for communications. This chapter presents a new approach to develop a chatbot system, applying ML to address the issue of accessing and managing information efficiently for the academic and industry sectors. It is a thrust area to maximize model accuracy and convergence rate. A chatbot is designed to make a discussion between human beings and machines. To identify the sentences, the system has been programmed with expertise. Following that, a decision is taken as a response to a query. The response idea is based on matching the user's supplied sentence. In this chapter, an expert system is developed for the college inquiry desk with a chatbot using natural language processing (NLP) as well as reinforcement‐learning (RL) algorithms. The proposed approach is based on experience learning to provide academic support services with chatbots. Here, customer experience cases are added to the chatbot to improve the connection and utilization of best practices for constant information handling.