Artificial Intelligence Tutorial

 AI is a technique that enables machines to mimic human behavior. Artificial Intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages. After completion of this tutorial you are able to 

  1. Summarize the characteristics of AI that make it useful to real-world problems. 
  2. Analyze different search techniques and predicate logic in artificial Intelligence. 
  3. Interpret knowledge representation and symbolic reasoning using different rules. 
  4. Apply the basic knowledge on learning and reinforcement learning. 
  5. Make use of the power of AI in Natural language processing as an advanced Application of AI.

Here are detailed index 

UNIT - I(Introduction to AI, Problems, Problem Spaces and Search)

  1. Definition and Importance of Artificial Intelligence
  2. Machine learning and deep learning are sub fields of AI
  3. Types of Learning in Artificial Intelligence
  4. Categorization of intelligent systems
  5. Application of AI
  6. History of Artificial Intelligence
  7. Some of the cross domains of Artificial intelligence
  8. Current Trends in AI
  9. Defining the Problem as a State space Search
  10. Production Systems
  11. Problem Characteristics
  12. Production system characteristics
  13. Issues in the Design of Search Programs

Part-I:(Heuristic Search Techniques)

  1. Generate-and-test
  2. Hill Climbing
  3. Best-First Search
  4. Problem Reduction
  5. Constraint Satisfaction
  6. Means-Ends Analysis.

Part-II(Knowledge Representation Using Predicate Logic)

  1. Representing Simple Facts in logic
  2. Representing Instance and Isa Relationships
  3. Computable Functions and Predicates
  4. Resolution.



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