ARTIFICIAL INTELLIGENCE (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: Describe what is AI and identify concept of intelligent agent; Explain various intelligent search algorithms to solve the 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 of Artificial Intelligence;
2. Uninformed Search Strategies;
3. Informed Search Strategies;
4. Local Search Algorithm & Optimization Problem;
5. Adversarial Search;
6. Constraint Satisfaction Problems;
7. Logical Agent;
8. First Order Logic & Inference in FOL I;
9. First Order Logic & 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.