The Artificial Intelligence course will cover the following:
Introduction to AI
Definitions, Goals of AI, AI Approaches, AI Techniques, Branches of AI,Applications of AI.
Problem Solving, Search and Control Strategies:
General problem solving, Search and control strategies, Exhaustive searches, Heuristic search techniques, Constraint satisfaction problems (CSPs) and models.
Knowledge representation, KR using predicate logic, KR using rules.
Learning Systems:
Rote learning, Learning from example: Induction, Explanation Based Learning (EBL), Discovery, Clustering, Analogy, Neural net and genetic learning, Reinforcement learning.
Expert Systems:
Knowledge acquisition, Knowledge base, Working memory, Inference engine, Expert system shells, Explanation, Application of expert systems.
Fundamentals of Neural Networks:
Research history, Model of artificial neuron, Neural networks architectures, Learning methods in neural networks, Single-layer neural network system, Applications of neural networks.