CSE307 - Artificial Intelligence


Spring'2011, Faculty of Computer Science, IBA - Karachi
Credit Hours: 3

This course provides an overview of the theoretical and practical aspects of designing intelligent computer systems. Students are expected to implement the concepts learned during the course using standard and AI-specific programming languages and tools. The following topics are covered in the course:
  • Overview of Artificial Intelligence
    • Historical Perspective
    • AI in the Modern World
  • State Space Representation
  • Search Techniques
    • Uninformed (Best-first, Depth-first)
    • Informed (A*, Best-first)
    • Search in Games
    • Minimax, Alpha-Beta Pruning
  • Machine Learning
    • Classification Trees
    • Na├»ve Bayes
    • Neural Networks
  • Logic
    • Propositional Logic
    • Predicate Logic
    • Logical Inference
  • Probabilistic Reasoning/Bayesian Networks
    • Knowledge Elicitation
    • Inference in BNs
  • Miscellaneous Topics (depending upon the availability of time)
    • Evolutionary Computation
    • Introduction to Robotics
    • Natural Language Processing

Prerequisites:
  • CSE205: Data Structures and Abstraction
  • MTS201: Logic and Discrete Structures

Text Book
  • Tim Jones, Artificial Intelligence: A Systems Approach, 2007.

Reference Books
  • Ben Coppin, Artificial Intelligence Illuminated, 2004.
  • Kevin Korb and Ann Nicholson, Bayesian Artificial Intelligence, 2003
  • Steven Rabin, AI Game Programming Wisdom 3, 2005.
  • Steve Rabin, AI Game Programming Wisdom 4, 2008

Grading
Term Exam
30 (15 + 15)
Final
40
Assignment
7.5
Quiz
7.5
Project
15

Software Tools