Introduction to Artificial Intelligence
Lecture Plan
Teaching Plan : https://drive.google.com/file/d/1dL4r7J9pronnaHp8eMedeml8eOo- i8FI/view?usp=sharing
Course Syllabus: https://drive.google.com/file/d/134Cu4UxgDc4v1rCm0zb- 2dGDV7BEq5fJ/view?usp=sharing
TOTAL : 45 LECTURE HOURS
Reference: TB1:
Stephen Lucci, Danny Kopec. Artificial Intelligence in the 21st Century. A Living Introduction. Mercury Learning and Information. 2nd Edition. 2016
UNIT-I Overview of Artificial Intelligence Chapter1: pp. 1-34 from TB1,, Total Hours : 07
| S.No. | Topic | No of Lecture Hours | Resources |
| 1 | Introduction and foundations of Artificial Intelligence, The Turing Test, Strong AI Versus Weak AI | 2 | Introduction Presentation The Turing Test Strong AI Versus Weak AI |
| 2 | Heuristics, Identifying Problems Suitable for AI | 2 | Heuristics DemoJug Problem |
| 3 | Applications and Methods, Early History of AI | 2 | Applications and Methods |
| 4 | Recent History of AI to the Present, AI In the New Millennium | 1 | History of AI |
UNIT-II Chapter 2: Uninformed Search: pp. 45 – 65 from TB1 Chapter 2: Informed Search pp. 75 – 100 from TB1 Total Hours : 12
| S.No. | Topic | No of Lecture Hours | Resources |
| 1 | Introduction: Search in Intelligent Systems, State-Space Graphs | 2 | Demo- MiniFalseCoinProblem |
| 2 | Generate-and-Test Paradigm, Uninformed Search: Blind Search Algorithm – Depth first search, Breadth first search | 3 | Presentation Generate-and-Test Paradigm Demo-4QueenPlacementBacktrack Presentation2 DFS BFS Implementation-BFS-DFS |
| 3 | Informed Search: Introduction, Heuristics | 2 | Presentation-HillClimbing-BestFirstSearch |
| 4 | Informed Search Algorithms – Finding Any Solution | 2 | Video-HillClimbing-BestFirstSearch |
| 5 | The Best-First Search, The Beam Search | 1 | Beam Search |
| 6 | Additional Metrics for Search Algorithms, Informed Search – Finding An Optimal Solution, Function | 2 | Branch and Bound A* Search |
UNIT – III
Chapter 4: pp. 111-126 from TB1 Total Hours : 6
| S.No. | Topic | No. of Lecture Hours | Resources |
| 1 | Search Using Games: Introduction, Game Trees and Minimax Evaluation | 2 | Presentation Video VideoChapter4-GameSearch, Video-TicTacToe-Minimax |
| 2 | Minimax With Alpha-Beta Pruning | 1 | Heuristic Evaluation with Minimax in Tic-tac-toe |
| 3 | Variations and Improvements To Minimax | 1 | Variations and improvements in Minimax |
| 4 | Games of Chance and the Expectiminimax Algorithm | 2 | GameofChance-Expectiminimax GameTheoryPrisonnerDilemma |
UNIT – IV Chapter 5: pp. 138-158 from TB1 Total Hours : 13
| S.No. | Topic | No of Lecture Hours | Resources |
| 1 | Introduction, Logic and Representation | 1 | Presentation |
| 2 | Propositional Logic | 2 | Presentation |
| 3 | Predicate Logic – Introduction | 2 | Presentation |
| 4 | Several Other Logics | 2 | |
| 5 | Uncertainty and Probability | 1 | |
| 6 | Knowledge representation | 1 | Presentation |
| 7 | Graphical Sketches and the Human Window, Graphs and the Bridges of Königsberg Problem | 1 | Presentation |
UNIT – V Chapter 7: pp. 126-208 from TB1.
| S.No. | Topic | No of Lecture Hours | Resources |
| 1 | Production Systems: Introduction, Background, basic examples | 2 | Presentation |
| 2 | Production Systems and Inference Methods | 2 | Presentation |
| 3 | Production Systems and Cellular Automata | 1 | Presentation |
| 4 | Stochastic Processes and Markov Chains | 1 | Presentation |
| 5 | Basic Features and Examples of Expert System | 1 | Presentation |