Artificial Intelligence (AI)
Explore intelligent agents, planning, and reasoning across realβworld tasks.
Explore intelligent agents, planning, and reasoning across realβworld tasks.
History, scope, applications beyond ML
Reactive, Limited Memory, Symbolic AI, Expert Systems
Propositional & Predicate Logic
Facts, Rules, Semantic Networks
Forward & Backward Chaining
DFS, BFS, Uniform Cost Search
Maze Solver using DFS/BFS in Python
State Space Representation
Greedy, A* Algorithm
Minimax Algorithm
Optimizing Minimax
Sudoku Solver, N-Queens
STRIPS, Goal Stack Planning
Tic-Tac-Toe AI (Minimax + Alpha-Beta)
Architecture, knowledge base, inference engine
if-then rules, forward chaining
Simple Expert System in Python (Medical Diagnosis / Career Guidance)
Tokenization, stemming, parsing
Pattern Matching with Regex in AI
Ontologies & Frames
Rule-Based Chatbot (no ML, just patterns & logic)
Fuzzy Logic & Decision Making
Types, agent architectures
Path planning, obstacle avoidance β without ML
Multi-Agent Systems & Swarm Intelligence
Automated Reasoning & Theorem Proving
Ethical AI & Symbolic AI vs. Statistical AI
Fuzzy Logic Based Smart Fan System
Choose One: Expert System for Career Guidance / AI-based Rule-Driven Chatbot / AI Maze/Tower of Hanoi Solver / Game AI (Checkers, Chess-lite, etc.)
Project Presentation, Documentation & Wrap-Up