Artificial Intelligence: VOLUME II

Thinking of starting your career in Artificial Intelligence?

Then you have landed in the right place.

The overall aim of this crash course Artificial Intelligence is to explore and examine key concepts, methods and techniques used in the Artificial Intelligence practical usage and also to look at the organisation, the group, the individual and their interaction within the confines of the artificial intelligence implementation lifecycle.

Artificial intelligence (AI) is a research field in computer science, which studies how to transfer (or impact) the human intelligence and (/or) logical behaviours to the computer machines. The ultimate goal of Artificial intelligence is to make or develop computer systems that can independently and autonomously learn, plan, strategies, and solve real-life problems. Due to the extensive and unrelenting studies that have been carried out in this magnificent field (of computer science) for more than half a century, systems are now built that can stand the test of intelligence with human beings. Examples of such intelligent systems include self-driving cars, online robotic teaching agents, intelligent home service agents, autonomous planning agents, Deep Blue IBM system (famously known for defeating a world chess champion) etc.

This book is Part II of the II Parts series, in this introductory course on AI, we have studied the most fundamental knowledge for understanding artificial intelligence, from the part I. Also, in the first 10 chapters of this introductory course, we have covered the fundamental and foundational principles driving the design, development, and implementation of intelligent systems. The topics discussed included AI fundamentals and methodology; historical background; Applications and impact of AI; Intelligent Agents; Problem Solving; Basic and Advanced Search Strategies.

The succeeding chapters in this Part II series will introduce the reader to more advanced forms of AI, which includes: knowledge representation; First-Order Logic; Uncertain Knowledge and Reasoning; Making Simple and Complex Decisions. The reader will also learn ‘how to’ use Artificial intelligence with the practical case studies and walk-through examples to practice. We will go through the usage of Artificial intelligence within Digital World such as using Artificial Intelligence in Online Platforms, Marketplaces Platforms, Social Media Platform, Gaming Platforms and much more.

The main goal of the course is to equip you with the tools to tackle new AI problems you might encounter in life.

What Will You Learn?

The main purpose of this course is to provide the most fundamental knowledge on AI to the reader so that they can understand what the Artificial Intelligence (‘AI’) is all about.

Course Objectives

• To have an appreciation for artificial intelligence and an understanding of both the triumphs of AI and the principles fundamental to those accomplishments.
• To have an appreciation for the core principles which are essential to the design of artificial intelligence systems.
• To have an elementary adeptness in a traditional artificial intelligence language which includes an ability to write simple programs.
• To have an understanding of the basic search strategies, as well as more advanced search strategies and fundamental issues hovering over intelligent agents and their environments.
• To have an elementary understanding of (some of the) more advanced topics of artificial intelligence such as knowledge representation, reasoning, first-order logic, and decision-making.

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Table of Contents

Chapter 9 Beyond Classical Search
Chapter 10 Adversarial Search and Constraint Satisfaction Problem (CSP)
Chapter 11 Knowledge Representation
Chapter 12 First-Order Logic
Chapter 13 Uncertain Knowledge and Reasoning
Chapter 14 Making Simple Decisions
Chapter 15 Making Complex Decisions