Rule-based Python system with forward and backward chaining inference engines. Communication between the system and the user has been enhanced with the Sun Valley theme for the Tkinter GUI toolkit. Users can load existing knowledge bases, are prompted to answer questions to narrow down options, and the system can draw conclusions based on new data.
Build a rule-based expert system with three main modules:
- Knowledge base: Structured facts and rules of a certain context
- Inference engine: Algorithm that dynamically draws conclusions based on known and new facts from both knowledge base and new user inputs
- Graphical user interface: Visual guidance for user that allows effective communication between user and algorithm.
AutomotiveInferenceSystem_demo.mp4
- The objective of this project was to create an inference engine that stores relationships based on a knowledge base containing facts and rules within a given context.
- This engine dynamically presents itself both in areas of knowledge and in new knowledge retrieval through interactive user questions and data storage.
- The expert system was developed using the Python programming language and a graphical interface built with the Tkinter library, using the Sun Valley theme to ensure uniformity and operation on MacOS, Windows, and Linux.
- The generated system is recognized as having the capacity to facilitate decision-making in a way directly proportional to the stored knowledge.
This project was assigned as the first partial exam of our Intelligent Languages college course (3rd year, fall semester)