BCS751
ARTIFICIAL INTELLIGENCE LAB
1. Implement Breadth First Search (BFS) for a given graph or maze.
2. Implement Depth First Search (DFS) for a tree or graph structure.
3. Solve the 8-Puzzle Problem using A* Search Algorithm.
4. Implement Hill Climbing Algorithm for numerical optimization or pathfinding.
5. Implement Simulated Annealing Algorithm for constraint-based search problems.
6. Solve Water Jug Problem using state-space search (BFS or DFS).
7. Write Prolog programs to define family relationships using predicates.
8. Implement 4-Queens Problem in Prolog using backtracking.
9. Implement Unification Algorithm in Python or Prolog.
10. Implement Forward and Backward Chaining in a rule-based system (manual or code-based).
11. Demonstrate Resolution in Propositional Logic through a basic example (e.g., proving a theorem).
12. Remove punctuation and stop words from a paragraph using nltk.
13. Perform stemming and lemmatization on user-input text.
14. Apply POS (Part of Speech) tagging using NLTK on a given sentence.
15. Build a simple text classifier using NLTK (e.g., classify messages as spam/ham).
16. Implement Tic-Tac-Toe game with a basic AI opponent.
17. Implement Min-Max (Minimax) Algorithm for decision making in turn-based games.
18. Enhance the game with Alpha-Beta Pruning to optimize Min-Max.
19. Simulate a Vacuum Cleaner Agent that intelligently cleans a 2D environment.
20. Build a simple chatbot using rules or pre-trained logic (can use regex or basic intent matching).
21. Design a Constraint Satisfaction Problem solver, e.g., Sudoku, or Map Coloring.
22. Perform simple Bayesian reasoning for a probability-based decision problem (e.g., medical diagnosis).