Lecture 1: Introduction to Artificial Intelligence

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1 Lecture 1: Introduction to Artificial Intelligence

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Lecture 1: Introduction to Artificial Intelligence. What is AI? . The branch of computer science called Artificial Intelligence is said to have been born at a conference held at Dartmouth, USA, in 1956 The scientists attending that conference represented several - PowerPoint PPT Presentation

Transcript of Lecture 1: Introduction to Artificial Intelligence

Page 1: Lecture 1: Introduction to Artificial Intelligence

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Lecture 1: Introduction to Artificial Intelligence

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What is AI?

• The branch of computer science called Artificial Intelligence is said to have been born at a conference held at

Dartmouth, USA, in 1956

• The scientists attending that conference represented several different disciplines: mathematics, neurology,

psychology, electrical engineering, etc

• They had one thing in common: They all were trying to use the recently developed computers to simulate various aspects of human intelligence

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What is AI?

• Artificial Intelligence may be defined as the branch of computer science that is concerned with the automation of intelligent behavior

• An exact definition of intelligence is not easy to formulate

• However, there are some general abilities which are universally considered as intelligent

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What is AI?

According to Douglas Hofstadter these are:

- To respond to situations very flexiblyIf the same response is exhibited each time, the behavior is called mechanical. To survive in changing environments, one need to exhibit innovative behavior (e.g. art of begging)

- To make sense out of ambiguous or contradictory messagesWe understand such messages because our knowledge

and experience allows us to place them in context. (e.g. time flies like an arrow, buy this washing powder

versus buy that washing powder)

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What is AI?

- To recognize the relative importance of different elementsof a situation(e.g. quality versus price of a commodity)

- To find similarities between situations despite differenceswhich may separate them(e.g. chairs in two different pictures)

- To draw distinctions between situations despite similaritieswhich may link them(e.g. differences in two cars)

These abilities are largely due to knowledge and experience,which allows you to place an information in its wider context

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What is AI?

Another definition of intelligence:

It is the ability to - perceive inter-relationship of facts- learn and understand from experience- acquire and retain knowledge- respond quickly and successfully to a new

situation

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What is AI?

Turing test was proposed in 1950.

It is a test to decide whether or not a particular machine is intelligent.

Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes

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What is AI?

- Contact only through monitor and keyboard- Machine tries to pose as a human- If the player cannot distinguish between human and

machine, then machine is considered intelligent Revised Turing Test: A human converses with an unseen

respondent and attempts to determine whether it is a man or machine. If the computer fools you into thinking that it is a human, than that machine is intelligent

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What is AI?

Sometimes it is possible to program computers to carry on shallow conversations, in limited areas, and thus fool unsuspecting humans into believing that they are addressing other humans.

Example: Program ELIZA simulating a psychiatrist.Person: I miss my childrenELIZA: “Why do you miss your children?”

or “ Tell me more about your family” ELIZA is programmed to ask pre-determined questions

and parrot segments of your responses back to you. Hence Turing test may not be such a good judge of machine intelligence after all

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What is AI?

This leads us to the issue of “understanding”

Even though a machine may be exhibiting intelligent behaviour, it does not “understands” what it is doing

Searle’s Chinese Room Example

Strong and Weak AI

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Major AI Areas

1. Expert SystemsAn ES is a computer program designed to act as an expert

in a particular domain (area of expertise). It typically includes a sizeable knowledge base, consisting of facts about the domain and rules for application to those facts. Medical (e.g. PXDES,

MYCIN) and Agriculture (e.g. AGREX)2. Natural Language Processing

Goal is to enable people and computers to communicate in ordinary or natural English.

- Comprehension of natural language: Keyboard input (e.g. MS Word

Processor), speech recognition (e.g. IBM VoiceType Dictation , BBN corporation: voice

activated browsers, speaker identification for security and Operetta™)

- Generation of natural language.

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Major AI Areas

3. Machine learning Field of study that gives computer the ability to learn

without being explicitly programmed (Arthur Samuel, 1956)

ML learning provides best methods for developing particular kinds of software, in applications where:

1. Application is too much complex for people to manually design the algorithm. For instance, soft- wares for sensor-based prediction tasks such as speech recognition and computer vision.

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Major AI Areas

3. Machine learning Field of study that gives computer the ability to learn

without being explicitly programmed (Arthur Samuel, 1956) ML learning provides best methods for developing particular kinds of software, in applications where:

2. Applications require that the software customize to its operational environment after it is fielded. For example, speech recognition system that customize to the user who purchase the software or recommenders

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Major AI Areas

4. Robotics and Computer VisionFactory automationAutonomous vehiclesRobots: Electromechanical devices programmed

to perform manual tasks. Not all robots are intelligent. Some are pre-programmed by conventional techniques and are dumb. An intelligent robot usually includes some kind of sensory apparatus that allows it to respond to changes in its environment.

Computer Vision: it is field that include methods for acquiring, processing, analyzing and understanding images in order to produce numerical and symbolic information. For example, medical image processing is an application of computer vision