Tribhuvan University

Institute of Science and Technology

Bachelor of Science in Computer Science and Information Technology

Course Title: Artificial Intelligence

Course no: CSC261

Semester: IV

Nature of course: Theory + Lab

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 8 + 8

Credit Hours: 3

Course Description : The course introduces the ideas and techniques underlying the principles and design of artificial intelligent systems. The course covers the basics and applications of AIincluding: design of intelligent agents, problem solving, searching, knowledge representation systems, probabilistic reasoning, neural networks, machine learning and natural language processing.

Course Objective : The main objective of the course is to introduce concepts of Artificial Intelligence. The general objectives are to learn about computer systems that exhibit intelligent behavior, design intelligent agents, identify AI problems and solve the problems, design knowledge representation and expert systems, design neural networks for solving problems, identify different machine learning paradigms and identify their practical applications.

Course Contents:
Laboratory Works:

Student should write programs and prepare lab sheet for mostoftheunits in the syllabus. Majorly, students should practice design and implementation of intelligent agents and expert systems, searching techniques, knowledge representation systems and machine learning techniques. Students are also advised to implement Neural Networks for solving practical problems of AI. Students are advised to use LISP, PROLOG, andany other high level languagelike C, C++, Java, etc. The nature of programmingcan be decided bytheinstructorand student as per their comfort. The instructors have to prepare lab sheets for individual units covering the conceptof the units as per the requirement. The sample lab sessions can be as following descriptions;

Unit II: Intelligent Agents (4 Hrs)-

  • Write programs for implementing simple intelligent agents.

Unit III: Problem Solving by Searching (12Hrs)-

  • Write programs for illustrating the concepts of
    1. Uninformed Searchlike DFS, BFS, etc.
    2. Informed Searchlike Greedy Best First, A*, etc.
    3. GameSearchlike MiniMax Search
  • Write programs for constraint satisfaction problems like water jug, n-queen problem, cryptoarithmatic problem,etc.

Unit IV: Knowledge Representation (12Hrs)-

  • Write programs for illustrating the concepts knowledge representation systems
    1. rule based(program with if then rules)
    2. predicate logic(using predicates like in Prolog)
    3. frames(using concepts of class)
    4. semantic nets (using concepts of graph)

Unit V: Machine Learning(10Hrs)-

  • Write programfor implementing Naive Bayes.
  • Write programfor implementing Neural Networks for realization of AND, OR gates.
  • Write programfor implementing Backpropagation Learning.

Unit VI: Applications of AI(7Hrs)-

  • Write programfor implementing expert systems like disease prediction, weather forecasting etc.
  • Use library tools like NLTK to illustrate concepts of Natural Language Processing.

Text Books:
  • Stuart Russel and Peter Norvig, Artificial Intelligence A Modern Approach, Pearson
Reference Books:
  • George F. Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Benjamin/Cummings Publication
  • E. Rich, K. Knight, Shivashankar B. Nair, Artificial Intelligence, Tata McGraw Hill.
  • D. W. Patterson, Artificial Intelligence and Expert Systems, Prentice Hall.
  • P. H. Winston, Artificial Intelligence, Addison Wesley.