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Course Content
Syllabus
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Syllabus
Lecture Notes
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Syllabus
Lesson Plan
UNIT 1 – INTRODUCTION
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Definition – Future of Artificial Intelligence
Characteristics of Intelligent Agents
Typical Intelligent Agents
Problem Solving Approach to Typical AI problems
Revision Additional Short Question and Answers
UNIT 1 – 2 Marks
MCQs – UNIT 1
Assignment1 - Case Study on Tesla Autopilot: An Intelligent Agent-Based Self-Driving System
UNIT 2
Problem solving Methods – Search Strategies- Uninformed – Informed – Heuristics
Local Search Algorithms and Optimization Problems
UNIT 2 – INVESTIGATIVE SMART PRACTICES
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Problem solving Methods – Search Strategies- Uninformed – Informed – Heuristics
Local Search Algorithms and Optimization Problems
Searching with Partial Observations
Constraint Satisfaction Problems
Constraint Propagation
Backtracking Search
Game Playing – Optimal Decisions in Games
Alpha – Beta Pruning
Stochastic Games
Unit 2 – 2 Marks
Backtracking 13 Mark QP and Answer
UNIT 3 – LAWS AND PRIVACY CONCERNS
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Knowledge Representation First Order Predicate Logic
Prolog Programming
Prolog – Unification
Forward Chaining-Backward Chaining
Resolution in AI
Knowledge Representation
Ontological Engineering Concepts
Unit 3 – 2 Marks
UNIT 4 – DATA ACQUISITION AND REPORT WRITING
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Software Agents Architecture for Intelligent Agents
Agent communication
Negotiation and Bargaining
Argumentation among Agents
Trust and Reputation in Multi-agent systems
23CAE711 – ARTIFICIAL INTELLIGENCE
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