Artificial Intelligence Tutorial

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What is Artificial Intelligence Tutorial?

Artificial Intelligence Tutorial provides knowledge on concepts of Artificial Intelligence. It explains about various Artificial Intelligence concepts in detail to understand in simple and easy steps.

Audience

This tutorial is targeted to the students at beginner level who wish to seek learn Artificial Intelligence.

Prerequisites

To learn this tutorial one must have the basic knowledge of Computer Science and familiar with Mathematics, Languages, Science, Mechanical or Electrical engineering will be an added advantage.

Artificial Intelligence Tutorial: List of Topics

• Introduction
  • What Is “artificial Intelligence”
  • Paths To Artificial Intelligence
  • Objections To Artificial Intelligence
  • Conceptual Metaphor, Analogy And Thought Experiments
  • Design Principles For Autonomous Agents
• Agents And Environments
  • What Is An Agent?
  • Agent-oriented Design Versus Object-oriented Design
  • A Taxonomy Of Autonomous Agents
  • Desirable Properties Of Agents
  • What Is An Environment?
  • Environments As N-dimensional Spaces
  • Virtual Environments
  • How Can We Develop And Test An Artificial Intelligence System?
• Frameworks For Agents And Environments
  • Architectures And Frameworks For Agents And Environments
  • Standards For Agent-based Technologies
  • Agent-oriented Programming Languages
  • Agent Directed Simulation In Netlogo
  • The Netlogo Development Environment
  • Agents And Environments In Netlogo
• Behaviour
  • What Is Behaviour?
  • Reactive Versus Cognitive Agents
  • Emergence, Self-organisation, Adaptivity And Evolution
  • The Frame Of Reference Problem
  • Stigmergy And Swarm Intelligence
  • Implementing Behaviour Of Turtle Agents In Netlogo
  • Boids
• Communication
  • Communication, Information And Language
  • The Diversity Of Human Language
  • Communication Via Communities Of Agents
  • Communicating Behaviour
  • The Small World Phenomenon And Dijkstra’s Algorithm
  • Using Communicating Agents For Searching Networks
  • Entropy And Information
  • Calculating Entropy In Netlogo
  • Language Modelling
  • Communicating Meaning
• Search
  • Search Behaviour
  • Search Problems
  • Uninformed (blind) Search
  • Implementing Uninformed Search In Netlogo
  • Search As Behaviour Selection
  • Informed Search
  • Local Search And Optimization
• Knowledge
  • Knowledge And Knowledge-based Systems
  • Knowledge As Justified True Belief
  • Different Types Of Knowledge
  • Some Approaches To Knowledge Representation And Ai
  • Knowledge Engineering Problems
  • Knowledge Without Representation
  • Representing Knowledge Using Maps
  • Representing Knowledge Using Event Maps
  • Representing Knowledge Using Rules And Logic
  • Reasoning Using Rules And Logic
  • Knowledge And Reasoning Using Frames
  • Knowledge And Reasoning Using Decision Trees
  • Knowledge And Reasoning Using Semantic Networks
• Intelligence
  • The Nature Of Intelligence
  • Intelligence Without Representation And Reason
  • What Ai Can And Can’t Do
  • The Need For Design Objectives For Artificial Intelligence
  • What Are Good Objectives?
  • Some Design Objectives For Artificial Intelligence
  • Towards Believable Agents
  • Towards Computers With Problem Solving Ability