Artificial Intelligence

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ARTIFICIAL INTELLIGENCE BE04043011
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Code: BE04043011 Credits: 3 Semester 4 AI & DS

Artificial Intelligence

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Artificial Intelligence Syllabus — Unit-wise Content

The official GTU curriculum for Artificial Intelligence (subject code BE04043011) as prescribed for AI & DS · Semester 4 divides the course into 12 units, covering 61 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 (BE04043011)

Unit 1 Introduction

  • The AI Problems
  • The Underlying Assumption
  • AI techniques
  • The Level of The Model
  • Criteria For Success 2 5

Unit 2 Problems, State Space Search & Heuristic Search Techniques

6 lecture hours

  • Defining The Problems As A State Space Search
  • Production Systems
  • Production Characteristics
  • Production System Characteristics and Issues in the Design of Search Programs
  • Hill Climbing
  • Best-First Search
  • Problem Reduction
  • Constraint Satisfaction
  • Means-Ends Analysis

Unit 3 Knowledge Representation

6 lecture hours

  • Representations And Mappings
  • Approaches To Knowledge Representation
  • Representation Simple Facts In Logic
  • Representing Instance and Isa Relationships
  • Computable Functions and Predicates
  • Procedural versus Declarative Knowledge
  • Logic Programming
  • Forward versus Backward Reasoning

Unit 4 Symbolic Reasoning Under Uncertainty

  • Introduction to Nonmonotonic Reasoning
  • Logics for Non-monotonic Reasoning 6 15

Unit 5 Probabilistic Reasoning

3 lecture hours

  • Probability And Bays’ Theorem
  • Certainty Factors and Rule Base Systems
  • Bayesian Networks
  • Dempster- Shafer Theory
  • Fuzzy Logic

Unit 6 Game Playing

  • MinMax Search Procedure
  • Alpha-Beta Cut-offs
  • Iterative deepening. 2 5

Unit 7 Planning

3 lecture hours

  • The Blocks World
  • Components Of a Planning System
  • Goal Stack Planning
  • Nonlinear Planning Using Constraint Posting
  • Hierarchical Planning
  • Reactive Systems

Unit 8 Natural Language Processing

3 lecture hours

  • Syntactic Processing
  • Semantic Analysis
  • Discourse And Pragmatic Processing
  • Spell Checking

Unit 9 Connectionist Models

4 lecture hours

  • Introduction: Hopfield Network
  • Learning In Neural Network
  • Application Of Neural Networks
  • Recurrent Networks
  • Distributed Representations
  • Connectionist AI And Symbolic AI

Unit 10 Expert Systems

  • Representing and Using Domain Knowledge
  • Expert System Shells
  • Knowledge Acquisition. 2 5

Unit 11 Genetic Algorithms

4 lecture hours

  • A Peek into the Biological World
  • Genetic Algorithms (GAs)
  • Significance of the Genetic Operators
  • Termination Parameters

Unit 12 Introduction to Prolog

4 lecture hours

  • Converting English to Prolog Facts and Rules
  • Prolog Terminology
  • Control Structures
  • Arithmetic Operators
  • Matching in Prolog
  • Lists Program Name: Bachelor of Engineering Level: UG Subject Code: BE04043011 Subject Name: Artificial Intelligence w.e.f.2024-25 http://syllabus.gtu.ac.in/ Pageno.3of5

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