A Simple Animal Recognition Expert System

This project presents a MATLAB implementation of a basic animal recognition expert system. The system utilizes a rule-based inference engine to classify 7 distinct animal species, with the knowledge base structured around 15 logical rules that define animal characteristics and relationships. The implementation typically involves creating a forward-chaining inference mechanism where MATLAB's logical operators and conditional statements evaluate animal features against the rule set. Key components include a facts database storing observed attributes and a rule interpreter that matches patterns to draw conclusions. The system architecture supports straightforward expansion by adding new animals and corresponding rules to enhance recognition accuracy and applicability. For implementation, developers would structure rules using nested if-then statements or switch-case constructs, with array operations handling feature matching efficiently.