This document outlines the presentation topics for an artificial intelligence course given by Bharat Bhushan, an assistant professor at RLSY College in Ranchi, India. The presentation covers 5 units: an introduction to AI, problem solving and searching techniques, knowledge representation, and dealing with uncertainty. Some of the specific techniques and topics that will be discussed include the Turing test, intelligent agents, search algorithms like A* and alpha-beta pruning, knowledge representation schemes like semantic nets and frames, probabilistic reasoning, and parsing techniques.
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Artificial Intelligence
UNIT-1 : INTRODUCTION
Introduction to Artificial Intelligence
Background and Applications
Turing Test and Rational
Agent approaches to AI
Introduction to Intelligent Agents
Their structure
Behavior and environment.
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Artificial Intelligence
UNIT- 2
Problem Solving and Searching Techniques
Problem Characteristics
Production Systems
Control Strategies,
Breadth First Search
Depth First Search
Hill climbing and its Variations
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Artificial Intelligence
Heuristics Search Techniques
Best First Search
A* algorithm
Constraint Satisfaction Problem
Means-End Analysis
Introduction to Game Playing
Min-Max and Alpha-Beta pruning
algorithms.
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Artificial Intelligence
UNIT- 3
Knowledge Representation
Introduction to First Order Predicate Logic
Resolution Principle
Unification
Semantic Nets
Conceptual Dependencies, Frames, and
Scripts
Production Rules
Conceptual Graphs
Programming in Logic (PROLOG)
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Artificial Intelligence
UNIT- 4
Dealing with Uncertainty and Inconsistencies
Maintenance System
Default Reasoning
Probabilistic Reasoning
Bayesian Probabilistic
Inference
Possible World Representations.
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Artificial Intelligence
UNIT- 5
Dealing with Uncertainty and Inconsistencies
Parsing Techniques
Context-Free and Transformational
Grammars
Recursive and Augmented Transition
Nets.