Beekman5 std ppt_14

2002 Prentice Hall

Chapter 14

Is Artificial Intelligence Real?

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Topics

Thinking machines – the concept and the controversy

How computers play (and win) games

Computers that Speak and translate human language

Expert systems and robots at work

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Thinking about Thinking Machines

If you ask 10 people to define intelligence, you’re likely to get 10 different answers, including some of these:

The ability to learn from experience The power of thought The ability to reason The ability to perceive relations The power of insight The ability to use tools Intuition

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Can Machines Think?

A machine may be deemed intelligent when

it can pass for a human being

in a blind test.

—Alan Turing

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What Is Artificial Intelligence

Artificial intelligence is the study of ideas which enable computers to do the things that make people seem intelligent.

—Patrick Henry Winston, in Artificial Intelligence

These definitions commonly appear in today’s popular press:

Artificial intelligence is the study of how to make computersdo things at which, at the moment, people are better.

Artificial intelligence is the study of the computationsthat make it possible to perceive, reason, and act.—Patrick Henry Winston, in Artificial Intelligence

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What Is Artificial Intelligence

Two common approaches to AI include:

One approach attempts to use computers to simulate human mental processes. For example, an AI expert might ask people to describe how they solve a problem and attempt to capture their answers in a software model.

The second, more common, approach to AI involves designing intelligent machine independent of the way people think. According to this approach, human intelligence is just one possible kind of intelligence.

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Opening Games

Much of the early AI work focused on games because they were easy to represent in the computer’s digital memory, they had clearly defined rules, and the goals were unmistakable.

Game researchers could focus on the concrete question “How can I create a program that wins consistently?”

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Opening Games

AI techniques developed by game researchers are still used today in a variety of applications. These techniques include: Searching Heuristics Pattern Recognition Machine Learning

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Natural Language Communication

Since the earliest days of computing, scientists have dreamed of machines that could communicate in natural languages like English, Russian, and Japanese.

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Natural Language Communication

Types of Natural language applications include:

Machine Translation Traps Conversation without communication Nonsense and common sense

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Machine Translation Traps

A parsing program (or parser) analyzes sentence structure and identify each word according to whether it was a subject, verb, or other part of speech; another program would look up each word in a translation dictionary and substitute the appropriate word.

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Conversation without communication

Similar lessons emerged from Joseph Weizenbaum’s work with ELIZA, one of the first software programs to converse in a limited form of natural language.

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Nonsense and common sense

Every language has a syntax—a set of rules for constructing sentences from words. In a programming language, the syntax rules are exact and unambiguous.

However, natural-language parsing programs have to deal with rules that are vague, ambiguous, and contradictory.

“Time flies like an arrow.”

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Knowledge Bases and Expert System

The human brain isn’t particularly good at storing and recalling facts, but excels at manipulating knowledge.

Computers, on the other hand, are better at handling data than knowledge.

Consequently, Artificial intelligence researchers have developed techniques for representing knowledge in computers.

The computer can’t tell you the emotional story. It can give youthe exact mathematical design, but what’s missing is the eyebrows.

—Frank Zappa

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Knowledge Bases and Expert System

Knowledge Bases contain a system of rules for determining and changing the relationship among those facts. Facts stored in a database are rigidly organized in categories; ideas stored in a knowledge base can be reorganized as new information changes their relationships.

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Knowledge Bases and Expert System

An expert system is a software program designed to replicate the decision-making process of a human expert. At the foundation of every expert system is a knowledge base representing ideas from a specific field of expertise.

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Expert Systems in Action

The first successful expert systems were developed around medical knowledge bases.

The business community has been more enthusiastic than the medical community in its use of expert systems. Some examples of expert systems in action include:

American Express uses an expert system to automate the process of checking for fraud and misuses of its no-limit credit card.

Blue Cross/Blue Shield of Virginia an expert system automates insurance claim processing.

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Expert Systems in Perspective

From the following examples it should be clear that expert systems offer many advantages. An expert system can perform these tasks:

Help train new employees Reduce the number of human errors Take care of routine tasks so workers can focus on more

challenging job Provide expertise when no experts are available Preserve the knowledge of experts after those

experts leave an organization.

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Pattern Recognition:Making Sense of the World

Pattern recognition involves identifying recurring patterns in input data with the goal of understanding or categorizing that input.

Applications include:

Image Analysis Optical Character Recognition Automatic Speech Recognition Talking Computers Neural Networks

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Pattern Recognition:Making Sense of the World

Image analysis is the process of identifying objects and shapes in a photograph, drawing, video, or other visual image.

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Pattern Recognition:Making Sense of the World

Optical character recognition (OCR) software locates and identifies printed characters embedded in images—it “reads” text. This is no small task for a machine, given the variety of typefaces and styles in use today.

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Pattern Recognition:Making Sense of the World

Automatic speech recognition systems use pattern recognition techniques similar to those used by vision and OCR systems, including these:

Segmentation of input sound patterns into individual words and phonemes

Expert rules for interpreting sounds Context “experts” for dealing with ambiguous sounds Learning from a human trainer

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Pattern Recognition:Making Sense of the World

Many computer applications speak like humans by playing prerecorded digitized speech and other digitized sounds stored in memory or disk.

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Pattern Recognition:Making Sense of the World

Neural networks (or neural nets) are distributed, parallel computing systems inspired by the structure of the human brain. Instead of a single, complex CPU, a neural network uses a network of a few thousand simpler processors called neurons.

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The Robot Revolution

A robot is a computer-controlled machine designed to perform specific manual tasks. A robot’s central processor might be a microprocessor embedded in the robot’s shell, or it might be a supervisory computer that controls the robot from a distance.

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The Robot Revolution

Robots offer several advantages: Robots can work 24 hours a day,

365 days a year, without vacations, strikes, sick leave, or coffee breaks.

Robots are effective at doing repetitive jobs in which bored, tired people are prone to make errors and have accidents.

Robots are ideal for jobs that are dangerous, uncomfortable, or impossible for human workers.

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AI Implications andEthical Questions

Experts believe that scientists will eventually create artificial beings that are more intelligent than their creators …..

a prospect with staggering implications.

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