Principles of Artificial Intelligence


 UNIT I

  • Introduction to AI, History of Artificial Intelligence, 
  • Applications of AI in the real world(Gaming, Computer Vision, Expert Systems, NLP, Robotics & others. 
  • AI techniques, 
  • Problem Solving: Production Systems, State Space Search, 
  • Depth First Search, Breadth First Search, 
  • Heuristic Search, Hill Climbing, 
  • Best First Search, best-first search, A*, Problem Reduction, AO*, 
  • Constraint Satisfaction, Means-End Analysis.

UNIT II

  • Knowledge representation, 
  • Knowledge representation using Predicate logic, 
  • Propositional logic, Inferences, 
  • First-Order Logic, Inferences, 
  • Unification, Resolution, Natural Deduction, 
  • Procedural versus declarative knowledge, 
  • Logic programming, forward versus backward reasoning.

UNIT III

  • Reasoning, 
  • Introduction to Uncertainty, 
  • Bayesian Theory, Bayesian Network, 
  • Dempster-Shafer Theory. 
  • Overview of Planning and its Components. 
  • Overview of Learning and basic Techniques. 
  • Introduction of Fuzzy Reasoning and Neural Networks.

UNIT IV

  • Game Playing and Current Trends in AI, 
  • MinMax search procedure, 
  • Alpha-Beta Cutoffs, 
  • Game Development using AI, 
  • Applications of AI, 
  • Emerging Trends in AI Research in various domains.


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