Offered:
Pre-requisite: CSE221
Concepts of artificial intelligence, rationality, intelligent agents and their structures. Problem representation; task environments, search strategies, constraint satisfaction problems, constraint propagation, rule chaining, inference and learning in intelligent systems; systems of general problem solving, game playing, expert consultation, recognition, understanding and translation. Use of heuristic vs. algorithmic programming; cognitive simulations- vs. machine intelligence; study of some expert systems such as robotics and understanding. Solving problems in AI language.
Course Objectives are:
1. Introduce the concept of Artificial Intelligence, rationality.
2. Analyze different problem-solving strategies for informed, uninformed problems, deterministic or stochastic games, and constraint satisfaction problem.
3. Present different algorithms and the analysis of complexity, optimality and completeness of these algorithms.
4. Develop the critical skill to formulate problems and strategies to solve problems.
5. Introduce the concept of uncertain knowledge and probabilistic reasoning.
6. Introduce probabilistic and logic models so the students will be able to use these models in various decision-making problems.
7. Introduce the basic concept of machine learning.
1. Artificial Intelligence A Modern Approach ,Stuart Russel, Peter Norvig,1995,Third,Pearson Education,978-0-13-604259-4
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