AGENT:
A program that performs some information gathering or processing task in the background. Typically, an agent is a given a very small and well-defined task.
Although the theory behind agents has been around for some time, agents have become more prominent with the recent growth of the Internet. Many companies now sell software that enables you to configure an agent to search the Internet for certain types of information.
In computer science, there is a school of thought that believes that the human mind essentially consists of thousands or millions of agents all working in parallel. To produce real artificial intelligence, this school holds, we should build computer systems that also contain many agents and systems for arbitrating among the agents' competing results.
ARTIFICIAL INTELLIGENCE:
The branch of computer science concerned with making computers behave like humans. The term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology. Artificial intelligence includes
games playing: programming computers to play games such as chess and checkers
expert systems: programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms)
natural language: programming computers to understand natural human languages
neural networks: Systems that simulate intelligence by attempting to reproduce the types of physical connections that occur in animal brains
robotics: programming computers to see and hear and react to other sensory stimuli
Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behavior). The greatest advances have occurred in the field of games playing. The best computer chess programs are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated world chess champion Gary Kasparov in a chess match.
In the area of robotics, computers are now widely used in assembly plants, but they are capable only of very limited tasks. Robots have great difficulty identifying objects based on appearance or feel, and they still move and handle objects clumsily.
Natural-language processing offers the greatest potential rewards because it would allow people to interact with computers without needing any specialized knowledge. You could simply walk up to a computer and talk to it. Unfortunately, programming computers to understand natural languages has proved to be more difficult than originally thought. Some rudimentary translation systems that translate from one human language to another are in existence, but they are not nearly as good as human translators. There are also voice recognition systems that can convert spoken sounds into written words, but they do not understand what they are writing; they simply take dictation. Even these systems are quite limited -- you must speak slowly and distinctly.
In the early 1980s, expert systems were believed to represent the future of artificial intelligence and of computers in general. To date, however, they have not lived up to expectations. Many expert systems help human experts in such fields as medicine and engineering, but they are very expensive to produce and are helpful only in special situations.
Today, the hottest area of artificial intelligence is neural networks, which are proving successful in a number of disciplines such as voice recognition and natural-language processing.
There are several programming languages that are known as AI languages because they are used almost exclusively for AI applications. The two most common are LISP and Prolog.
CYBER:
A prefix used in a growing number of terms to describe new things that are being made possible by the spread of computers. Cyberphobia, for example, is an irrational fear of computers. Cyberpunk is a genre of science fiction that draws heavily on computer science ideas. Cyberspace is the non-physical terrain created by computer systems.
EXPERT SYSTEM:
A computer application that performs a task that would otherwise be performed by a human expert. For example, there are expert systems that can diagnose human illnesses, make financial forecasts, and schedule routes for delivery vehicles. Some expert systems are designed to take the place of human experts, while others are designed to aid them.
Expert systems are part of a general category of computer applications known as artificial intelligence. To design an expert system, one needs a knowledge engineer, an individual who studies how human experts make decisions and translates the rules into terms that a computer can understand.
FUZZY LOGIC:
A type of logic that recognizes more than simple true and false values. With fuzzy logic, propositions can be represented with probabilities of truthfulness and falsehood. Fuzzy logic has proved to be particularly useful in expert system and other artificial intelligence applications. It is also used in some spell checkers to suggest a list of probable words to replace a misspelled one.
GENETIC PROGRAMMING:
A type of programming that utilizes the same properties of natural selection found in biological evolution. The general idea behind genetic programming is to start with a collection of functions and randomly combine them into programs; then run the programs and see which gives the best results; keep the best ones (natural selection), mutate some of the others, and test the new generation; repeat this process until a clear best program emerges.
LISP is a popular language for genetic programming.
HANDWRITING RECOGNITION:
The technique by which a computer system can recognize characters and other symbols written by hand. In theory, handwriting recognition should free us from our keyboards, allowing us to write and draw in a more natural way. It is considered one of the key technologies that will determine the ultimate success or failure of PDAs and other hand-held devices. To date, however, the technology has had only limited success. This is partly because it is still a young technology and is not as fast or accurate as it needs to be. Another reason for its slow acceptance, however, is that the keyboard is in fact more convenient in many situations. Many people can write much faster with a keyboard than they can by hand.
NATURAL LANGUAGE:
A human language. For example, English, French, and Chinese are natural languages. Computer languages, such as FORTRAN and C, are not.
Probably the single most challenging problem in computer science is to develop computers that can understand natural languages. So far, the complete solution to this problem has proved elusive, although a great deal of progress has been made. Fourth-generation languages are the programming languages closest to natural languages.
NEURAL NETWORK:
A type of artificial intelligence that attempts to imitate the way a human brain works. Rather than using a digital model, in which all computations manipulate zeros and ones, a neural network works by creating connections between processing elements, the computer equivalent of neurons. The organization and weights of the connections determine the output.
Neural networks are particularly effective for predicting events when the networks have a large database of prior examples to draw on. Strictly speaking, a neural network implies a non-digital computer, but neural networks can be simulated on digital computers.
The field of neural networks was pioneered by Bernard Widrow of Stanford University in the 1950s. To date, there are very few commercial applications of neural networks, but the approach is beginning to prove useful in certain areas that involve recognizing complex patterns, such as voice recognition.
OPTICAL CHARECTER RECOGNITION:
Often abbreviated OCR, optical character recognition refers to the branch of computer science that involves reading text from paper and translating the images into a form that the computer can manipulate (for example, into ASCII codes). An OCR system enables you to take a book or a magazine article and feed it directly into an electronic computer file.
All OCR systems include an optical scanner for reading text, and sophisticated software for analyzing images. Most OCR systems use a combination of hardware (specialized circuit boards) and software to recognize characters, although some inexpensive systems do it entirely through software. Advanced OCR systems can read text in large variety of fonts, but they still have difficulty with handwritten text.
The potential of OCR systems is enormous because they enable users to harness the power of computers to access printed documents. OCR is already being used widely in the legal profession, where searches that once required hours or days can now be accomplished in a few seconds.
PATTERN RECOGNITION:
An important field of computer science concerned with recognizing patterns, particularly visual and sound patterns. It is central to optical character recognition (OCR), voice recognition, and handwriting recognition.
ROBOTICS:
The field of computer science and engineering concerned with creating robots, devices that can move and react to sensory input. Robotics is one branch of artificial intelligence.
Robots are now widely used in factories to perform high-precision jobs such as welding and riveting. They are also used in special situations that would be dangerous for humans -- for example, in cleaning toxic wastes or defusing bombs.
Although great advances have been made in the field of robotics during the last decade, robots are still not very useful in everyday life, as they are too clumsy to perform ordinary household chores.
VOICE RECOGNITION:
The field of computer science that deals with designing computer systems that can recognize spoken words. Note that voice recognition implies only that the computer can take dictation, not that it understands what is being said. Comprehending human languages falls under a different field of computer science called natural language processing.
A number of voice recognition systems are available on the market. The most powerful can recognize thousands of words. However, they require an extended training session during which the computer system becomes accustomed to a particular voice and accent. Such systems are said to be speaker dependent.
Most systems also require that the speaker speak slowly and distinctly and separate each word with a short pause. These systems are called discrete speech systems. It will be many years before voice recognition systems support continuous speech so that users can speak naturally.
Because of their limitations and high cost, voice recognition systems are used only in a few specialized situations. For example, such systems are useful in instances when the user is unable to use a keyboard to enter data because his or her hands are occupied or disabled. Instead of typing commands, the user can simply speak into a headset.
Posts
