Artificial Intelligence

Module
1

Introduction
Version 2 CSE IIT, Kharagpur

1.1 Instructional Objectives
– Understand the definition of artificial intelligence
– Understand the different faculties involved with intelligent behavior
– Examine the different ways of approaching AI
– Look at some example systems that use AI
– Trace briefly the history of AI
– Have a fair idea of the types of problems that can be currently solved by computers
and those that are as yet beyond its ability
.

We will introduce the following entities:
• An agent
• An intelligent agent
• A rational agent

We will explain the notions of rationality and bounded rationality.
We will discuss different types of environment in which the agent might operate.
We will also talk about different agent architectures.

On completion of this lesson the student will be able to
• Understand what an agent is and how an agent interacts with the environment.
• Given a problem situation, the student should be able to
o identify the percepts available to the agent and
o the actions that the agent can execute.
• Understand the performance measures used to evaluate an agent

The student will become familiar with different agent architectures
• Stimulus response agents
• State based agents
• Deliberative / goal-directed agents
• Utility based agents

The student should be able to analyze a problem situation and be able to
• identify the characteristics of the environment
• Recommend the architecture of the desired agent








Version 2 CSE IIT, Kharagpur

Lesson
1

Introduction to AI
Version 2 CSE IIT, Kharagpur

1.1.1 Definition of AI
What is AI ?
Artificial Intelligence is concerned with the design of intelligence in an artificial device.
The term was coined by McCarthy in 1956.

There are two ideas in the definition.
1. Intelligence
2. artificial device
What is intelligence?

– Is it that which characterize humans? Or is there an absolute standard of judgement?
– Accordingly there are two possibilities:
– A system with intelligence is expected to behave as intelligently as a human
– A system with intelligence is expected to behave in the best possible manner
– Secondly what type of behavior are we talking about?
– Are we looking at the thought process or reasoning ability of the system?
– Or are we only interested in the final manifestations of the system in terms of
its actions?

Given this scenario different interpretations have been used by different researchers as
defining the scope and view of Artificial Intelligence.
1. One view is that artificial intelligence is about designing systems that are as
intelligent as humans.

This view involves trying to understand human thought and an effort to build
machines that emulate the human thought process. This view is the cognitive
science approach to AI.

2. The second approach is best embodied by the concept of the Turing Test.
Turing held that in future computers can be programmed to acquire abilities
rivaling human intelligence. As part of hi s argument Turing put forward the idea
of an 'imitation game', in which a human being and a computer would be
interrogated under conditions where the interrogator would not know which was
which, the communication being entirely by textual messages. Turing argued that
if the interrogator could not distinguish them by questioning, then it would be
unreasonable not to call the computer intelligent. Turing's 'imitation game' is now
usually called 'the Turing test' for intelligence.


Version 2 CSE IIT, Kharagpur

Turing Test
Consider the following setting. There are two rooms, A and B. One of the rooms
contains a computer. The other contains a human. The interrogator is outside and
does not know which one is a computer. He can ask questions through a teletype and
receives answers from both A and B. The interrogator needs to identify whether A or
B are humans. To pass the Turing test, the m achine has to fool the interrogator into
believing that it is human. For more details on th e Turing test visit the site
http://cogsci.ucsd.edu /~asaygin/tt/ttest.html

3. Logic and laws of thought deals with st udies of ideal or rational thought process
and inference. The emphasis in this case is on the inferencing mechanism, and its
properties. That is how the system arri ves at a conclusion, or the reasoning behind
its selection of actions is very important in this point of view. The soundness and
completeness of the inference mechanisms