Artificial Intelligence
Subject Overview
Artificial Intelligence introduces intelligent agents and problem-solving, uninformed and informed search (BFS, DFS, A*, Minimax, Alpha-Beta pruning), knowledge representation via propositional and predicate logic with forward/backward chaining, planning and handling uncertainty (probabilistic reasoning, fuzzy sets), and surveys AI domains — machine learning, computer vision, robotics, NLP and expert systems — along with their legal and ethical issues. A 3-credit core theory paper.
Unit-wise Syllabus
4 units — click WhatsApp below to get the full notes for each
Unit 1: Introduction to AI
What AI is, intelligent agents and environments, the concept of rationality, agent structure, knowledge-based agents, the Wumpus World example, problem-solving agents
Unit 2: Advanced search techniques
Uninformed search (DFS, BFS, iterative deepening), informed search (Best First Search, A*, AO*), adversarial search (Minimax, Alpha-Beta pruning), constraint satisfaction problems and backtracking search, evolutionary search techniques and genetic algorithms
Unit 3: Logical reasoning and uncertainty
Propositional and first-order predicate logic, unification and lifting, forward/backward chaining, resolution, truth maintenance systems, introduction to planning (Blocks World, STRIPS), non-monotonic reasoning, probabilistic reasoning, introduction to fuzzy set theory
Unit 4: AI domains and applications
Introduction to machine learning, computer vision, robotics, natural language processing and deep neural networks, expert system architecture with case studies, legal and ethical issues in AI