Abstract:
Intelligent Systems (IS) are often complex to implement by their nature. This presents IS tutors with a problem if they want to encourage their students to explore practical implementation issues. If tutors wish to give students concise, easy to understand, practical examples of IS they are often forced to simplify systems to a point where their functionality is no longer realistic and may additionally hide important practical issues. Alternatively tutors may encourage students to build small but real systems. This requires students to possess advanced programming abilities and takes time, limiting what can be covered in other theoretical aspects of an IS course.
As the nature of computing degrees becomes more diverse, and with it the background of students sitting IS modules, a third alternative is preferred. This paper explores an alternative which provides a suite of programming tools designed to aid students' progress with practical symbolic computation. The paper describes these tools and demonstrates their efficacy in simplifying practical aspects of IS programming.
As the nature of computing degrees becomes more diverse, and with it the background of students sitting IS modules, a third alternative is preferred. This paper explores an alternative which provides a suite of programming tools designed to aid students' progress with practical symbolic computation. The paper describes these tools and demonstrates their efficacy in simplifying practical aspects of IS programming.