Expert Systems in AI

An expert system is a computer system that uses artificial intelligence (AI) algorithms to simulate the decision-making capabilities of a human expert. The four main components of an expert system are the knowledge base, search or inference engine, knowledge acquisition system, and user interface or communication system. The basic goal of an expert is to duplicate human experts and replace them with problem-solving. There are five main types of expert systems: rule-based systems, frame-based systems, fuzzy systems, neural systems, and neuro-fuzzy systems. A chatbot is a computer program that can mimic human conversation by using voice commands, text dialogues, or both. Chatbots can be integrated into any messaging service and are useful for providing easy and quick communication for users. Good chatbot development is dependent on the chatbot algorithm and the implementation approach employed by the chatbot developer. Today’s chatbot landscape is wide. Chatbots are not categorized as a distinct category but rather as part of a broader variety of expert systems. In this chapter, the authors summarize the expert system, technologies, and approaches used to design an AI-powered intelligent chatbot system. It will provide a space for the readers and the developers to understand the basics of expert systems and the fundamental concepts for developing a chatbot.