| Anna University CSE |

Artificial Intelligence - CS8691

Online Study Material, Lecturing Notes, Assignment, Reference, Wiki and important questions and answers

| Anna University CSE |

UNIT I INTRODUCTION

=> What is Artificial intelligence(AI)?
=> Production System

UNIT II PROBLEM SOLVING METHODS

UNIT III KNOWLEDGE REPRESENTATION

=> Game playing
=> Iterative Deepening
=> Knowledge Representation
=> Predicate Calculus
=> Predicate Logic
=> AI Resolution: Definition and Principle
=> Structured Represntation of Knowledge

UNIT IV SOFTWARE AGENTS

UNIT V APPLICATIONS

For Extra Reference

Artificial Intelligence Notes 1

=> What is Artificial Intelligence?
=> History of Artificial Intelligence(AI)
=> Components of Artificial Intelligence(AI)
=> Definition of Artificial intelligence
=> Weak And Strong Artificial Intelligence(AI)
=> Areas and Task Domain of Artificial Intelligence(AI)
=> Artificial Intelligence(AI) Technique
=> 7- Problem Characteristics
=> Production System: Characteristics, Features , Disadvantages
=> Algorithm of Problem Solving
=> Various Types of Artificial Intelligence Problems and their Solutions
=> Searching Algorithms - Artificial Intelligence(AI)
=> Uninformed Search
=> Breadth First Search (BFS): Concept, Implementation, Advantages, Disadvantages
=> Depth First Search (DFS): Concept, Implementation, Advantages, Disadvantages
=> Brute Force or Blind Search(BFS)
=> Greedy Search
=> Informed Search (Heuristic Search)
=> Best First Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
=> Branch and Bound Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
=> A* Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
=> AO* Search(Graph): Concept, Algorithm, Implementation, Advantages, Disadvantages
=> Hill Climbing Search Algorithm: Concept, Algorithm, Advantages, Disadvantages
=> Knowledge Based Systems
=> Type of Knowledge
=> Knowledge Acquisition Techniques
=> Knowledge representation
=> Properties for knowledge Representation
=> Syntax and semantics for Knowledge Representation
=> Types of Knowledge Representation
=> Human Associative Memory (HAM)
=> MIN-MAX Search Algorithm
=> Constraint Satisfaction Search Algorithm
=> Planning
=> Basic Components of a Planning System
=> Planning in State Space Search
=> Various Planning Techniques
=> Understanding in Artificial Intelligence
=> Natural Language Processing
=> Goals, Applications and Examples of Natural Language Processing(NLP)
=> ELIZA, HAL, LUNAR, SHRDLU System
=> The Chomsky Hierarchy of Grammars
=> Transformational Grammar
=> Case Grammars (FILLMORE’s Grammar)
=> Semantic Grammars
=> Context Free Grammar (CFG)
=> Parsing Process
=> Types of Parsing
=> Transition Network
=> Types of Transition Network
=> Learning - Artificial Intelligence
=> Classification of Learning
=> Multi Agent Learning
=> Explanation based Learning
=> Genetic Algorithm
=> Applications and Advantages of Genetic Algorithm
=> Neural Network
=> Features Of Artificial Network (ANN)
=> Types of Neural Networks
=> Feed Forward neural network
=> Back Propagation neural network
=> Clustering and Types of Clustering
=> Pattern Recognition
=> Expert System
=> Difference Between Expert System and Conventional System
=> The Development Process of an Expert System
=> Characteristics of an Expert System
=> Structure of an Expert System
=> Rule Based Architecture of an Expert System
=> Applications of Expert Sytem

Artificial Intelligence Notes 2

=> Artificial Intelligence(AI) Problem Solving
=> Intelligent Agent
=> Uninformed Search Strategies
=> Heuristics / Informed Search Strategies
=> Constraint Satisfaction Problems (CSPS)
=> Important Questions and Answers: Algorithm of Problem Solving
=> Logical Agents
=> Important Questions and Answers: Logical Agents
=> Planning With State Space Search
=> Partial Order Planning
=> Important Questions and Answers: Artificial Intelligence Planning
=> Uncertainty - Artificial Intelligence
=> Important Questions and Answers: Artificial Intelligence - Uncertainty
=> Learning from observation
=> Inductive Learning
=> Learning Decision Trees
=> Explanation Based Learning
=> Statistical Learning Methods
=> Reinforcement Learning
=> Important Questions and Answers: Artificial Intelligence Learning

Artificial Intelligence Notes 3

=> What is Artificial Intelligence(AI)?
=> Importance of Artificial Intelligence(AI)
=> Early work in Artificial Intelligence(AI)
=> Artificial Intelligence(AI) and related fields
=> Search and Control Strategies
=> Examples of search problems
=> Uniformed or Blind search
=> Informed search
=> Constraint Satisfaction Search
=> Heuristic Repair
=> Tabu Search
=> Simulated Annealing
=> Real-Time A*
=> Propositional and Predicate Logic
=> Semantics
=> Predicate Calculus
=> First-Order Predicate Logic(FOPL)
=> Modal Logics and Possible Worlds
=> Dempster- Shafer theory
=> Probabilistic Reasoning
=> Definition and importance of knowledge
=> Representation of knowledge
=> Knowledge Organization and Manipulation
=> Matching techniques
=> Structures used in Matching
=> Measure for Matching
=> Matching like Patterns
=> Partial Matching
=> The RETE matching algorithm
=> Knowledge Organization and Management
=> Indexing and retrieval techniques
=> Integrating knowledge and memory
=> Natural Language Processing
=> Artificial Intelligence: Grammars and Languages
=> Basic parsing techniques
=> Augmented Transition Networks
=> Chart Parsing
=> Semantic Analysis
=> Expert System Architecture
=> Rules for Knowledge Representation
=> Rule-Based Systems
=> Rule-Based Expert Systems
=> Architecture of an Expert System
=> Knowledge Engineering
=> CLIPS (C Language Integrated Production System)
=> Backward Chaining in Rule-Based Expert Systems
=> CYC

Artificial Intelligence Notes 4

=> What is Artificial intelligence(AI)?
=> Production System
=> Game playing
=> Iterative Deepening
=> Knowledge Representation
=> Predicate Calculus
=> Predicate Logic
=> AI Resolution: Definition and Principle
=> Structured Represntation of Knowledge
=> Knowledge Representation
=> Framework of Knowledge Representation (Poole 1998)
=> Knowledge Representation Schemes
=> Issues in Knowledge Representation
=> KR Using Predicate Logic
=> KR Using Rules
=> Planning and Machine Learning
=> Symbolic Reasoning
=> Statistical Reasoning
=> Probability and Bayes’ Theorem
=> Certainty Factors in Rule-Based Systems
=> Bayesian Networks and Certainty Factors
=> Dempster - Shafer Theory (DST)
=> Fuzzy Logic
=> Expert System
=> Expert System Characteristics
=> Expert System Features
=> Knowledge Acquisition
=> Knowledge Base (Representing and Using Domain Knowledge)
=> Inference Engine
=> Expert System Shells
=> Explanation - Expert System
=> Application of Expert Systems

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