B.E. (Automation and Robotics) Artificial Intelligence AI for Robots Syllabus - Mumbai University 2026

Discrete Mathematics, Data Structures

Module 1: Introduction to Artificial Intelligence

• Introduction, History of Artificial Intelligence, Intelligent Systems: Categorization of Intelligent System, Components of AI Program, Foundations of AI, Sub-areas of AI, Applications of AI, Current trends in AI.

Module 2: Intelligent Agents

• Agents and Environments, The concept of rationality, The nature of environment, The structure of Agents, Types of Agents, Learning Agent. Solving problem by Searching: Problem Solving Agent, Formulating Problems, Example Problems.

Module 3: Problem solving

• Uninformed Search Methods: Breadth First Search (BFS), Depth First Search (DFS), Depth Limited Search, Depth First Iterative Deepening (DFID), Informed Search Methods: Greedy best first Search, A* Search, Memory bounded heuristic Search. Local Search Algorithms and Optimization Problems: Hill climbing search Simulated annealing, Genetic algorithms. Adversarial Search: Game Playing, Min-Max Search, Alpha Beta Pruning to number of respective lecture hours mentioned in the curriculum.

Textbooks

• 1 Stuart J. Russell and Peter Norvig, “Artificial Intelligence: A Modern Approach”, Fourth Edition” Pearson Education, 2020.
• 2 Saroj Kaushik, “Artificial Intelligence”, Cengage Learning, First edition, 2011
• 3 George F Luger, “Artificial Intelligence” Low Price Edition, Fourth edition, Pearson Education.,2005
• 1 Nils J. Nilsson, Principles of Artificial Intelligence, Narosa Publication.
• 2 Deepak Khemani, A First Course in Artificial Intelligence, McGraw Hill Publication
• 3 Patrick H. Winston, Artificial Intelligence, 3rd edition, Pearson Education.
• 4 Elaine Rich and Kevin Knight, “Artificial Intelligence”, Third Edition, McGraw Hill Education,2017. U University of Mumbai