Artificial Intelligence Syllabus
This page provides detailed information about the Artificial Intelligence Syllabus, covering AI fundamentals, intelligent agents, search techniques, logical reasoning, machine learning, robotics, natural language processing, and expert systems, along with ethical and legal considerations.
Artificial Intelligence Syllabus
Unit 1 – Introduction to AI and Intelligent Agents
- Artificial Intelligence (AI)
- Intelligent Agents
- Agent and Environment
- Rationality
- Nature of Environment
- Structure of Agents
- Knowledge-Based Agents
- Wumpus World
- Problem-Solving Agents
Unit 2 – Advanced Search and Evolutionary Techniques
- Uninformed Search
- Depth First Search (DFS)
- Breadth First Search (BFS)
- Iterative Deepening Search
- Informed Search
- Best First Search
- A* Search
- AO* Search
- Adversarial Search
- Minimax Algorithm
- Alpha-Beta Pruning
- Constraint Satisfaction Problems (CSP)
- Backtracking Search
- Evolutionary Algorithms
- Genetic Algorithms
- Applications of Evolutionary Search
Unit 3 – Logical Reasoning and Uncertainty Handling
- Propositional Logic
- First-Order Predicate Logic (FOPL)
- Inference
- Unification and Lifting
- Forward Chaining
- Backward Chaining
- Resolution
- Truth Maintenance Systems
- Planning
- Blocks World Problem
- STRIPS
- Non-Monotonic Reasoning
- Probabilistic Reasoning
- Fuzzy Set Theory
Unit 4 – AI Domains, Applications, and Ethics
- Machine Learning
- Computer Vision
- Robotics
- Natural Language Processing (NLP)
- Deep Neural Networks (DNN)
- Expert Systems
- Expert System Architecture
- Case Studies in Expert Systems
- Legal Issues in AI
- Ethical Issues in AI