Simple Chatbot using Rule-Based AI

A simple chatbot using rule-based AI operates by following a set of predefined rules and patterns to respond to user input. Unlike more advanced AI models, it doesn’t learn or adapt from interactions. Instead, it uses “if-then” logic to generate responses based on keywords or specific phrases within a user’s input. For example, if a user says “Hello,” the chatbot might respond with “Hi! How can I help you today?” Rule-based chatbots work well for straightforward tasks, such as answering frequently asked questions or guiding users through fixed procedures, where the range of interactions is limited.

These chatbots typically rely on a decision tree or flowchart model to direct conversations, often implemented through natural language processing (NLP) libraries that match phrases to specific intents. While rule-based chatbots are less flexible than AI-powered models that can understand context, they are advantageous in applications where accuracy and control over responses are essential, such as customer service or initial screening in support channels. However, they may struggle with complex or varied input, as they lack the capability to learn from new data.