Artificial Intelligence
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Artificial Intelligence Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligence (subject code 2180703) as prescribed for Information Technology · Semester 8 divides the course into 14 units, covering 66 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 (2180703)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
- Hill Climbing
- Best-First Search
- Problem Reduction
- Constraint Satisfaction
- Means-Ends Analysis
Unit 3 Knowledge Representation Issues
- Representations And Mappings
- Approaches To Knowledge Representation
Unit 4 Using Predicate Logic
- Representation Simple Facts In Logic
- Representing Instance And Isa Relationships
- Computable Functions And Predicates
Unit 5 Representing Knowledge Using Rules
- Procedural Versus Declarative Knowledge
- Logic Programming
- Forward Versus Backward Reasoning
Unit 6 Symbolic Reasoning Under Uncertainty
- Introduction To Non- monotonic Reasoning
- Logics For Non-monotonic Reasoning
Unit 7 Statistical Reasoning
- Probability And Bays’ Theorem
- Certainty Factors And Rule-Base Systems
- Bayesian Networks
- Dempster- Shafer Theory
- Fuzzy Logic
Unit 8 Weak Slot-and-Filler Structures
- Semantic Nets
Unit 9 Strong Slot-and-Filler Structures
- Conceptual Dependency
- Scripts, CYC
Unit 10 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 11 Understanding
- What is understanding?
- What makes it hard?
- As constraint satisfaction
Unit 12 Natural Language Processing
- Syntactic Processing
- Semantic Analysis
- Discourse And Pragmatic Processing
- Spell Checking
Unit 13 Connectionist Models
- Introduction: Hopfield Network
- Learning In Neural Network
- Application Of Neural Networks
- Recurrent Networks
- Distributed Representations
- Connectionist AI And Symbolic AI
Unit 14 Introduction to Prolog
- Introduction To Prolog: Syntax and Numeric Function
- Basic List Manipulation Functions In Prolog
- Predicates and Conditional
- Output and Local Variables
- Iteration and Recursion
- Property Lists and Arrays
- Miscellaneous Topics
- LISP and Other AI Programming Languages
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