8:27 AM
Unit I: Introduction to AI (10)
1.1 Introduction
to Artificial Intelligence
1.2 Brief
history of AI,
1.3 Applications
of Artificial Intelligence,
1.4 Definition
and importance of Knowledge,
1.5 Learning
Agent and it’s performance measure
1.6 Problems
Definition, Real life problems and well-defined problem
Unit II: Search Techniques (20)
1.1 Uninformed
search techniques: depth first search, breadth first search, depth limit
search, Iterative deepening search,
1.2 Heuristics
search techniques: Greedy Best first search, A* search, Hill Climbing, Game
playing, Adversarial search techniques-mini-max procedure, alpha beta pruning
Unit III: Knowledge, Reasoning and Planning (20)
3.1 Formal
logic-connectives: truth tables, syntax, semantics, tautology, validity,
well-formed-formula,
3.1 Propositional
Logic, Inference with PL: Resolution, Backward Chaining and Forward Chaining,
3.1 First
Order Predicate Logic(FOPL), quantification,
inference with FOPL: By converting into PL (Existential and universal
instantiation), Directly with FOPL (unification and lifting, resolution
Backward chaining, Forward Chaining),
3.1 Rule based
deduction system,
3.1 Statistical
Reasoning-Probability and Bayes' theorem and causal networks, reasoning in
belief network
Unit IV: Structured Knowledge Representation (10)
4.1 Representations
and Mappings,
4.2 Approaches
to Knowledge Representation, Issues in Knowledge Representation,
4.3 Semantic
nets, frames,
4.4 conceptual
dependencies and scripts
Unit V: Application of AI system in education (20)
5.1 Expert
Systems (Architecture, Expert system development process),
5.2 Application
of Expert system in education
5.3 Neural
Network (Mathematical model, get realization, Network structure)
5.4 Application
of Neural Network in education
5.5 Natural
Language Processing (Steps of NLP, parsing)
5.6 Application
of NLP in education
5.7 Basic
Concepts of Machine Learning and Visioning
5.8 Application
of Machine Learning in education