Artificial Intelligence
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Artificial Intelligence Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligence (subject code 3161608) as prescribed for ICT · Semester 6 divides the course into 9 units, covering 51 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3161608)Unit 1 What is AI?
- The AI Problems
- The Underlying Assumption
- What is an AI Techniques
- The Level Of The Model
- Criteria For Success
- Some General References
- One Final Word
Unit 2 Problems, State Space Search & Heuristic Search Techniques
- Defining The Problems As A State Space Search
- Production Systems
- Production Characteristics
- Production System Characteristics, And Issues In The Design Of Search Programs
- Additional Problems
- Generate-And- Test
- Hill Climbing
- Best-First Search
- Problem Reduction
- Constraint Satisfaction
- Means-Ends Analysis
- A* and AO* search
Unit 3 Logical Agents
- Knowledge–based agents
- The Wumpus world
- Propositional logic
- Propositional theorem proving
- Effective propositional model checking
- Agents based on propositional logic
- First Order Logic: Representation Revisited
- Syntax and Semantics of First Order logic
- Using First Order logic
Unit 4 Inference in First Order Logic
- Propositional Versus First Order Inference
- Forward Chaining
- Backward Chaining
Unit 5 Uncertainty – Acting under Uncertainty, Basic Probability Notation, The
- Axioms of Probability
- Inference Using Full Joint Distributions
Unit 6 Probabilistic Reasoning – Representing Knowledge in an Uncertain
- The Semantics of Bayesian Networks
- Efficient Representation of Conditional Distribution
- Exact Inference in Bayesian Networks
- Approximate Inference in Bayesian Networks Subject Code: 3161608 w.e.f
Unit 7 Game Playing
- Overview, and Example Domain : Overview
- Alpha-Beta Cut-off
- Iterative deepening
- The Blocks World
- Components of a Planning System
- Goal Stack Planning
- Nonlinear Planning Using Constraint Posting
- Hierarchical Planning
- Reactive Systems
- Other Planning Techniques
Unit 8 Statistical Learning Methods – Statistical Learning, Learning with
- Complete Data
- Learning with Hidden Variables: EM Algorithm
Unit 9 Introduction to Prolog
- Introduction To Prolog: Syntax and Numeric Function
- Basic List Manipulation Functions In Prolog
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