Course CS638 (July-Dec 2007)
Title Aritificial Intelligence
Instructor Dr. Deepak Khemani

Course Syllabus

  • Introduction: Overview and Historical Perspective; Turing test, Physical Symbol Systems and the scope of Symbolic AI; Agents.

  • Weak Methods: Search Methods, Heuristic Search, Goal Trees; Optimization, Probabilistic Methods; Game Trees; Planning and Constraint Satisfaction Problems - Waltz Algorithm.

  • Knowledge representation: Logic,  Conceptual Dependency Theory, and Frames; Theorem Proving, Forward Reasoning and Rete Networks; Backward Reasoning, Resolution Method and Logic Programming; Semantic Networks, Inheritance and Aggregation Hierarchies; Case Based Reasoning and Learning; Truth maintenance systems, Default and Probabilistic Reasoning, Dempster-Shafer Theory.

Text Books

  1. Russell, S., and Norvig, P., Artificial Intelligence: A Modern Approach, Prentice Hall, Englewood Cliffs, NJ, 1995.
  2. Winston, P. H., Artificial Intelligence, Addison-Wesley, Reading Massachusetts, 1992.
  3. Patterson, D.H., Introduction to Artificial Intelligence and Expert Systems, Prentice Hall of India, New Delhi, 2001.
  4. Charniak, E., and McDermott, D., Introduction to Artificial Intelligence, Addison-Wesley, Reading Massachusetts, 1984.
  5. Rich, E., and Knight, K., Artificial Intelligence, Tata McGraw Hill, New Delhi, 1991.