Page 8 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes Introduction

Artificial Intelligence (AI) is the intelligence of machines or software and is also a branch of
computer science that studies and develops intelligent machines and software. This field of
computer science, AI, is defined as “the study and design of intelligent agents” where an intelligent
agent is a system that perceives its environment and takes actions that maximize its chances of
success. It is also defined as “the science and engineering of making intelligent machines”.
AI research is highly technical and specialized, deeply divided into subfields that often fail to
communicate with each other. Some of the division is due to social and cultural factors: subfields
have grown up around particular institutions and the work of individual researchers. AI research
is also divided by several technical issues. There are subfields which are focused on the solution
of specific problems, on one of several possible approaches, on the use of widely differing tools
and towards the accomplishment of particular applications. There is no established unifying
theory or paradigm that guides AI research. Researchers disagree about many issues A few of
the most long standing questions that have remained unanswered are these: should artificial
intelligence simulate natural intelligence by studying psychology or neurology?

The central problems (or goals) of AI research include reasoning, knowledge, planning, learning,
communication, perception and the ability to move and manipulate objects. General intelligence
or “strong AI” is still among the field’s long term goals. Currently popular approaches include
statistical methods, computational intelligence and traditional symbolic AI. There are an
enormous number of tools used in AI, including versions of search and mathematical
optimization, logic, methods based on probability and economics, and many others. In this unit,
you will be able to understand the meaning of Artificial Intelligence, its goals and importance,
the early work and common techniques used in Artificial Intelligence.

1.1 What is AI?

Artificial intelligence (AI) is the science of programming computers to perform complex tasks
that normally require human intelligence. Artificial intelligence systems used in information
security applications include Artificial Neural Networks, expert systems and genetic algorithms.

AI is an emerging technology that has recently attracted considerable publicity. Many applications
are now under development. One simple view of AI is that it is concerned with devising computer
programs to make computers smarter. Thus, research in AI is focused on developing
computational approaches to intelligent behavior. This research has two goals:
1. Making machines more useful.
2. Understanding intelligence.

The computer programs with which AI is concerned are primarily symbolic processes involving
complexity, uncertainty, and ambiguity. These processes are usually those for which algorithmic
solutions do not exist and search is required. Thus, AI deals with the types of problem-solving
and decision-making that humans continually face in dealing with the world.

1.1.1 Goals of AI

The general problem of simulating (or creating) intelligence has been broken down into a
number of specific sub-problems. These consist of particular traits or capabilities that researchers
would like an intelligent system to display. The traits described below have received the most
attention.

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