RECENT TREND IN ARTIFICIAL INTELLIGENCE
WHICH AREA ARE SCIENTISTS FOCUSING THEIR RESEARCH ON?
A
large number of problems in the AI field have been associated with robotics.
In addition to the mechanical problems of getting a machine to make every
precise or delicate movements, there is the problem of determining the sequence
of movements. Much work in this area involves problem solving and planning.
One of the most useful ideas that has ever emerged from AI research is that
facts and rules can be represented separately from decision making alogorithms.
This realisation has had a profound effect both on the way that scientists
approach problems and on the engineering techniques used to produce AI systems.
By adopting a particular procedural element, called an inference engine, development of an AI system is reduced to obtaining and codifying sufficient rules and facts from the problem domain. This codification process is called knowledge engineering. Reducing system development to knowledge engineering has opened the door to non-AI practitioners. In additioon, business and industry have been recruiting AI scientists to build expert systems. An impediment to building even more useful systems is the problem of input.
To this end, much effort is currently being devoted to speech recognition, character recognition, machine vision, and natural language processing. A second problem is in obtaining knowledge, It has proven arduous to extract knowledge from an expert and then code it for use by the machine. To this end, efforts are currently being devoted to learning and knowledge acquisition. Following the idea of representing knowledge declaratively, logic programming, such as the computer language PROLOG, was developed. PROLOG is actually an inference engine that searches declared facts and rules to confirm or deny a hypothesis. A drawback of PROLOG is that it cannot be altered by the programmer. In the early 1980s, the Japanese government began a project to build powerful computers with hardware that makes logical inferences in the manner of PROLOG. They refer to such machines as fifth-generation computers.
Hopes for breakthroughs in AI hinge on a number of factors, such as the growing number of scientists involved in AI, the continuing identification of useful techniques, and advances in computer science, including Parallel Processing.
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