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From Discrete Mathematics to AI applications: A progression path for an undergraduate program in math

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

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From Discrete Mathematics to AI applications: A progression path for an undergraduate program in math

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  1. 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

  2. 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

  3. 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

  4. Computer Science Modules Math Modules Discrete Math and Logic Formal Specification Automata & Formal Lang. Proposed approach

  5. Three essential aspects fundamental concepts of AI computational language concepts that support AI and applications of AI

  6. 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

  7. Discrete Math • Data Structures • Discrete Structures - Sets - Sequences - Relations

  8. 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

  9. 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

  10. Prolog • Based on predicate logic • A logic programming language • Automatic Theorem Proving • Developed into a general purpose programming language for AI applications

  11. 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

  12. Categories of modules • Fundamentals • Computation • Applications • General Education • Additional Modules • Projects

  13. Categories of modules :Fundamentals • Graph Theory • Combinatorics • Discrete Math • Logic • Operating Systems • Operations Research • Introduction to AI

  14. Categories of modules :Computation • Data Structures • Algorithms • Formal Specification • Prolog • Theory of computation

  15. Categories of modules :Applications • Pattern Recognition • Expert Systems • Natural Language Processing • Automatic Theorem Proving • Robotics • Machine Intelligence • Human Computer Interaction

  16. Categories of modules :General Education • English • Biology • Philosophy • Pyschology

  17. Additional Modules • Calculus • Mathe. Statistics • Numerical Methods • Hardware Networking • Systems Software • Computer Architecture • DBMS • Physics • Computer vision • Fuzzy set &fuzzy logic

  18. Structure of the programme • Four year/8 semester • 15 weeks/sem • No. of modules?? • Credit points?? • Exit points??

  19. Pedagogy • Group work • Task based • Effort based • Individual effort • Self study • Blend of theory and practice • Exposure to real life problems

  20. 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

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