📘 Syllabus (CSE472 - Theory)

• Unit 1: INTRODUCTION TO AI
  • A. Foundation of AI, Goals of AI, History and AI course line
  • B. Introduction to Intelligent Agents; Environment; Structure of Agent
  • C. AI Solutions Vs Conventional Solutions; a philosophical approach; a practical approach
• Unit 2: PROBLEM SOLVING AGENTS
  • A. Problem solving using Search Techniques; Problems; Solutions; Optimality
  • B. Informed Search Strategies; Greedy Best-First; A* Search; Heuristic Functions
  • C. Uninformed Search Strategies; BFS; DFS; DLS; UCS; IDFS; BDS
• Unit 3: KNOWLEDGE & REASONING
  • A. Knowledge-Based Agents; Logic; First-Order Logic; Syntax-Semantics in FOL; Simple usage
  • B. Inference Procedure; Inference in FOL; Reduction; Inference Rules
  • C. Forward Chaining; Backward Chaining; Resolution
• Unit 4: LEARNING
  • A. Common Sense Vs Learning; Components; Representations; Feedback
  • B. Learning Types: Supervised; Unsupervised; Reinforcement Learning
  • C. Artificial Neural Networks: Introduction, types of networks; Single Layer and Multi-Layer Networks
• Unit 5: APPLICATIONS
  • A. AI Present & Future; application case studies on NLP, Image Processing
  • B. Robotics – Hardware; Vision; Navigation based case studies
  • C. Ambient Intelligence case studies

💻 Syllabus (CSP472 - Lab)

• Unit 1: Practical based on goal-based problems with LISP
  • 1. Introduction to Lisp, basic programming structures, and sample programs related to AI.
  • 2. Write a LISP function to compute the sum of squares.
  • 3. Write a LISP function to compute the difference of squares.
  • 4. Write a Recursive LISP function that returns the last element of a list.
  • 5. Write a Recursive LISP function that returns a list except the last element.
  • 6. Write a Recursive LISP function that returns the reverse of a list.
  • 7. Write a Recursive LISP function that removes the first occurrence of an atom from a list.
  • 8. Write a Recursive LISP function that appends two lists.
  • 9. Write a Recursive LISP function that merges two lists alternately.
  • 10. Write a function that computes factorial of a number.
  • 11. Write a function that evaluates a fully parenthesized infix expression.
  • 12. Write a function that performs DFS traversal of a binary tree.
• Unit 2: Practical related to Uninformed Search Algorithms
  • 1. Write a LISP/Python program for the Water Jug Problem.
  • 2. Write a LISP/Python program that determines if an integer is prime.
  • 3. Implement BFS and DFS on a graph in Python.
  • 4. Implement Uniform Cost Search on weighted graphs.
  • 5. Simulate Depth-Limited and Iterative Deepening Search.
  • 6. Apply Greedy BFS with heuristics.
  • 7. Implement A* search algorithm with heuristics.
  • 8. Solve Sudoku using backtracking and forward-checking.
• Unit 3: AGENT, KNOWLEDGE & REASONING
  • 1. Simulate a logic-based agent for the Wumpus World.
  • 2. Generate truth tables and evaluate logic expressions.
  • 3. Create inference engines using chaining techniques.
• Unit 4: APPLICATIONS
  • 1. Build and visualize decision trees using sklearn.
  • 2. Train a logistic regression model on a dataset.
  • 3. Implement K-Nearest Neighbors classifier.
  • 4. Use ensemble methods for classification.
  • 5. Build a simple neural network in NumPy.
  • 6. Train MLP using TensorFlow/Keras.
  • 7. Train CNN on MNIST/CIFAR-10 using Keras.
• Unit 5: Knowledge Representation, Reasoning & Course Project
  • 1. Introduction to PROLOG and program structure.
  • 2. PROLOG program to categorize animals (and similar examples).
  • 3. PROLOG solver for linear equation A*X + B = 0.
  • 4. PROLOG program for family relationships (father, mother, uncle, grandson, etc.).
  • 5. Build a simple chatbot in Python.
  • 6. Perform sentiment classification with NLTK/sklearn.
  • 7. Course Project Review-1: Problem Statement.
  • 8. Course Project Review-2: Design Specification.
  • 9. Course Project Review-3: Development & Results.

Evaluations Schemes

• Evaluations Schemes-for theory
• Evaluations Schemes-for Lab
• Search Algorithm Demos: BFS, DFS, A*
• Expert Systems in CLIPS
• Knowledge Base using Prolog

📚 Lectures

Theory lecture materials will be uploaded unit-wise. Each unit will include:

Lab

Lab details and experiments will be available here.

Important Dates

Quiz dates and instructions will be added soon.