What is AI? Intelligent Agents: Agents and environment, the concept of Rationality, the nature
of environment, the structure of Agents. Knowledge-Based Agents: Introduction to
Knowledge-Based Agents, The Wumpus World as an Example World. Problem-solving:
Problem-solving agents.

Uninformed Search: DFS, BFS, Iterative Deepening Search. Informed Search: Best First
Search, A* search, AO* search. Adversarial Search & Games: Two-player zero-sum games,
Minimax Search, Alpha-Beta pruning. Constraints and Constraint Satisfaction Problems
(CSPs), Backtracking search for CSP. Evolutionary Search Techniques: Introduction to
evolutionary algorithms, Genetic algorithms, Applications of evolutionary search in AI.

Logic: Propositional logic, First-order predicate logic, Propositional versus first-order
inference, Unification and lifting. Inference: Forward chaining, Backward chaining,
Resolution, Truth maintenance systems. Introduction to Planning: Blocks World problem,
Strips; Handling Uncertainties: Non-monotonic reasoning, Probabilistic reasoning,
Introduction to Fuzzy set theory.

Domains in AI: Introduction to Machine Learning, Computer Vision, Robotics, Natural
Language Processing, Deep Neural Networks, and their Applications. Expert Systems: The
architecture and role of expert systems include two case studies. Legal and Ethical Issues:
Concerns related to AI