The objective of this course is to introduce and teach the fundementals of problems, theories, algorithms and applications of Artificial Intelligence (AI). AI is a very fast-growning field that focuses on building intelligent systems that will have a great impact on every aera of industry, economy, and social life. The topics include definition and history of AI, problem solving via search, game playing, knowledge representation, propositional logic, first-order predicate logic, logical and probabilistic reasoning, planning, uncertain knowledge and reasoning, machine learning (popular machine learning algorithms, deep learning, reinforcement learning, and genetic algorithms), natural language processing, deep learning for natural language processing, computer vision and robotics.
Artificial Intelligence: A Modern Approach, 4th Edition, by Stuart Russell and Peter Norvig.(html).
- Speech and Language Processing by
Jurafsky and Martin, 2021
- G. F. Luger, Artificial Intelligence, Addison-Wesley, 2002.
|Evaluation Tool (*)||Weight in %|
- 1 Midterm
|1||Introduction and Intelligent Agents|
|2||Problem Solving by Searching|
|3||Adversarial Search and Games|
|4||Constraint Satisfaction Problems|
Inference in First-Order Logic
|8||Uncertain knowledge and reasoning|
Making Simple Decisions
Making Complex Decisions
|13||Natural Language Processing
Deep Learning for Natural Language Processing ..