About this course:

  • Course Name: Fundamentals of Artificial Intelligence
  • Course Code: ME 620
  • L-T-P-C : 3-0-0-6
  • Syllabus: Download
  • Course Type: Department Open Elective


    • Fundamentals of Artificial Intelligence

    Description:

    Course Objective: What does automatic scheduling or autonomous driving have in common with web search, speech recognition, and machine translation? These are complex real-world problems! Aim of artificial intelligence (AI) is to tackle these problems with rigorous mathematical tools. The objective of this course is to present an overview of the principles and practices of AI to address such complex real-world problems. The course is designed to develop a basic understanding of problem solving, knowledge representation, reasoning and learning methods of AI.

    Course Content/ Syllabus: Introduction: Scope; History, Trends and Future Directions. Problem Solving by Search: Production Systems and AI; Graph-Search Strategies: Uninformed Search, Heuristic Search Techniques; Constraint Satisfaction Problems; Stochastic Search Methods; Searching Game Trees: Minimax, Alpha-Beta Pruning. Knowledge Representation and Reasoning: Predicate Calculus in AI: Syntax and Semantics, Expressivity, Unification, Resolution; Resolution Refutation Systems; Situation Calculus. Reasoning under uncertainty: Notion of Uncertainty; Uncertain Knowledge and Reasoning, Probabilities; Bayesian Networks. Planning: Planning with State Space Search; Planning Graphs; Partial Order Planning. Decision Making: Sequential Decision Problems, Algorithms for optimal Policies. Machine Learning: Learning from Observations: Overview of different forms of Learning, Learning Decision Trees, Computational Learning Theory, Statistical Learning Methods, Neural Networks and Connectionist Learning.

    References:

    1. Patrick Henry Winston, Artificial Intelligence, Third Edition, Addison-Wesley Publishing Company, 2004.
    2. Nils J. Nilsson, Principles of Artificial Intelligence, Illustrated Reprint Edition, Springer Heidelberg, 2014.
    3. Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd Edition, PHI, 2009.
    4. Nils J. Nilsson, Quest for Artificial Intelligence, First Edition, Cambridge University Press, 2010.