200 likes | 377 Views
From Discrete Mathematics to AI applications: A progression path for an undergraduate program in math. Abdul Huq Middle East College of Information Technology, Sultanate of Oman huq@mecit.edu.om and Narayanan T. Ramachandran Middle East College of Information Technology, Sultanate of Oman
E N D
From Discrete Mathematics to AI applications: A progression path for an undergraduate program in math Abdul Huq Middle East College of Information Technology, Sultanate of Oman huq@mecit.edu.om and Narayanan T. Ramachandran Middle East College of Information Technology, Sultanate of Oman narayanan@mecit.edu.om
Approaches to AI • Can be approached in different ways.. • AI as a branch of Computer Science • AI’s strong links with Math • May be thought of as Applied Math • Clarification of Theoretical issues
AI and Math • The term AI has its roots in Math • Dominant role played by Mathematicians in the establishment of CS disciplines: Introduced by John McCarthy,Prof. of Math, Dartmouth College • There are Math departments with AI Groups • Use of technology in traditionally strong Mathematical subjects
Computer Science Modules Math Modules Discrete Math and Logic Formal Specification Automata & Formal Lang. Proposed approach
Three essential aspects fundamental concepts of AI computational language concepts that support AI and applications of AI
Component mapping with essential aspects • Discrete Math and Logic • Automata & Formal Lang. • Formal Specification • Prolog fundamental concepts of AI computational language concepts that support AI and applications of AI Natural Lang. Processing Expert System Robotics Auto-matic Theorem Proving
Discrete Math • Data Structures • Discrete Structures - Sets - Sequences - Relations
Logic • Propositional Logic • Predicate Logic • Logics of higher order • Fuzzy Logic • Useful in Knowledge Representation • There are researchers who consider logic as the most important factor in developing strategic, fundamental advances
VDM • A formal specification language • Specifies what needs to be done rather than how it is to be done • Based on predicate logic • Useful in program development and proving correctness of programs
Prolog • Based on predicate logic • A logic programming language • Automatic Theorem Proving • Developed into a general purpose programming language for AI applications
Key Features • Ensure a firm understanding of the basic tools and techniques that are required for AI applications • Instill knowledge in a spectrum of related subjects • Encourage Creativity in the process of developing solutions to a variety of problems • Provide opportunities to convert complex scenarios into various solvable parts and identify a solution from a list of known options • Increase ability to search for solutions • Develop computational skills that are needed in the industry • Develop the ability to reason logically, analytically and critically • Ensure that there is clear understanding of the role of AI specialists • Provide the necessary skills to appreciate different AI concepts, their use and rationale
Categories of modules • Fundamentals • Computation • Applications • General Education • Additional Modules • Projects
Categories of modules :Fundamentals • Graph Theory • Combinatorics • Discrete Math • Logic • Operating Systems • Operations Research • Introduction to AI
Categories of modules :Computation • Data Structures • Algorithms • Formal Specification • Prolog • Theory of computation
Categories of modules :Applications • Pattern Recognition • Expert Systems • Natural Language Processing • Automatic Theorem Proving • Robotics • Machine Intelligence • Human Computer Interaction
Categories of modules :General Education • English • Biology • Philosophy • Pyschology
Additional Modules • Calculus • Mathe. Statistics • Numerical Methods • Hardware Networking • Systems Software • Computer Architecture • DBMS • Physics • Computer vision • Fuzzy set &fuzzy logic
Structure of the programme • Four year/8 semester • 15 weeks/sem • No. of modules?? • Credit points?? • Exit points??
Pedagogy • Group work • Task based • Effort based • Individual effort • Self study • Blend of theory and practice • Exposure to real life problems
Learning outcomes of the programme On completion of the programme, student will be able to: • Formulate AI problems Mathematically • Apply standard Mathematical methods • Write code to implement solution procedures • Search for information in tackling advanced problems