People Innovation Excellence

ARTIFICIAL INTELLIGENCE (4 Credits)

Learning Outcomes:

On successful completion of this Course, students will be able to: Describe what is AI and identify the concept of intelligent agent; Explain various intelligent search algorithms to solve problems; Explain how to use knowledge representation in reasoning purpose; Demonstrate how to achieve a goal through a sequence of actions called planning; Apply various techniques to an agent when acting under certainty; Apply how to process natural language and other perceptual signs in order that an agent can interact intelligently with the world.

Topics:

  1. Introduction to Artificial Intelligence;
  2. Uninformed Search Strategies;
  3. Informed Search Strategies;
  4. Local Search Algorithm & Optimization Problems;
  5. Adversarial Search;
  6. Constraint Satisfaction Problems;
  7. Logical Agents;
  8. First Order Logic (FOL) & Inference in FOL I;
  9. First Order Logic (FOL) & Inference in FOL II;
  10. Classical Planning;
  11. Planning and Acting in the Real World;
  12. Knowledge Representation;
  13. Quantifying Uncertainty;
  14. Probabilistic Reasoning;
  15. Probabilistic Reasoning over Time;
  16. Making Simple Decisions;
  17. Making Complex Decisions;
  18. Learning from Examples I;
  19. Learning from Examples II;
  20. Knowledge in Learning;
  21. Learning Probabilistic Models;
  22. Reinforcement Learning;
  23. Natural Language Processing;
  24. Natural Language for Communication;
  25. Perception;
  26. Robotics.

 


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